A Study of the Factors that Affect Share Price Movements ...

A Study of the Factors that Affect Share

Price Movements of REITs in Malaysia

Wong Wen Yih

A Thesis Submitted for the Degree of

Master of Business (Research)

Coordinating Supervisor: Dr Lee Miin Huui

Associate Supervisor: Dr Fung Chorng Yuan

Faculty of Business, Design and Arts

Swinburne University of Technology

14 May 2020

I

Abstract

This thesis investigates both firm-specific and macroeconomic factors that drive the share price

movements of REITs in Malaysia. Also, it analyses the relationships between the selected

independent variables and M-REIT share prices. The identification of factors was carried out

through a literature review and synthesis, and a 3-stage variable selection process was

conducted so that only independent variables that would add the most value to the analysis

were put through to the analysis. 17 REITs listed on Bursa Malaysia were studied. The data

source spanned from 2008 to 2017 but for the M-REITs that were established after the year

2008, the data was compiled from their inauguration. Therefore, the panel dataset was

unbalanced. The data analysis was conducted using EViews and the results concluded that

market capitalisation, the price-earnings ratio, the interest rate and the shariah-compliance

dummy had a significant positive relationship while the dividend yield and the inflation rate

had a significant but negative relationship with M-REIT share prices. The findings suggest that

some widely held perceptions can be misleading. It is believed that this study extends the

research of the subject matter in the context of Malaysia and reduces the knowledge gap.

Knowing what drives the movements of M-REIT share prices reduces uncertainty and

strengthens the confidence of potential and existing investors to make more informed decisions

to invest in M-REITs, both conventional and shariah-compliant ones.

II

Declaration

I, Wong Wen Yih, declare that this thesis is the original report of my research which contains

no material that has been accepted or submitted formerly, in whole or in part, for any other

academic award except where reference is indicated in the thesis.

Wong Wen Yih

Faculty of Business, Design and Arts

Swinburne University of Technology

1 October 2019

III

Acknowledgement

Above all, I wish to express my utmost gratitude to my Father in Heaven for the completion of

this thesis, from whom I received the wisdom and strength to face the challenges that have

come my way. I would also wish to thank my coordinating supervisor, Dr Lee Miin Huui and

associate supervisor, Dr Fung Chorng Yuan for their continuous guidance, patience and support,

especially, when I had to apply for long leaves of absence to care for a family member. Last

but not least, I am thankful for my supportive and sacrificial parents who did not ask me to

give up on my Master’s Degree despite the family’s needs.

IV

Table of Contents

Page

Abstract I

Declaration II

Acknowledgement III

Table of Contents IV

List of Tables VIII

List of Diagrams IX

Chapter One: Introduction 1

1.1 Background of the Study 1

1.2 Differences between Equity and Mortgage REITs 3

1.3 Types of Malaysian Real Estate Investment Trusts (M-REITs) 5

1.3.1 Non-Shariah Compliant M-REITs 5

1.3.2 Shariah Compliant M-REITs 5

1.4 Problem Statement 10

1.5 Research Aims and Objectives 12

1.6 Research Questions 12

1.7 Structure of the Thesis 12

1.8 Summary 13

Chapter Two: Literature Review 14

2.1 Introduction 14

2.2 History and Prospects of the REIT Industry 14

2.2.1 The United States 14

2.2.2 Australia 16

2.2.3 Japan 17

2.2.4 Singapore 17

2.2.5 Malaysia 18

2.3 Factors that Drive the Movements of Share Prices in General 20

2.3.1 Firm-Specific Factors 24

2.3.2 Macroeconomic Factors 30

V

2.4 Factors that Drive the Movements of REIT Share Prices 33

2.4.1 Interest Rate and Inflation Rate 36

2.4.2 Earnings, Dividends and Net Income 39

2.4.3 Financial Leverage and Gearing 40

2.4.4 Net Asset Value 41

2.4.5 Market Capitalisation 43

2.5 Shariah-Compliance as a Firm-Specific Factor 45

2.6 Summary 50

Chapter Three: Methodology 51

3.1 Introduction 51

3.2 Research Philosophy 52

3.3 Research Framework 52

3.3.1 Identification of Factors through Literature Review and Synthesis 52

3.3.2 Quantitative and Non-Experimental Analysis 53

3.3.3 Panel Data Analysis 54

3.4 Variable Selection Criteria 55

3.5 Hypotheses 57

3.6 Conceptual Framework 57

3.7 Data Collection 60

3.7.1 Secondary Data and Data Source 60

3.7.2 Sample Selection and Limitations 61

3.8 Data Analysis 62

3.9 Summary 67

Chapter Four: Results and Findings 68

4.1 Introduction 68

4.2 Phase One: Identification of Factors through Literature Review and

Synthesis

68

4.3 Variable Selection Process 69

4.3.1 Stage One: Identification of Variables Analysed in Past Studies 69

4.3.2 Stage Two: Elimination based on Significance of Variables Analysed 70

(a) Non-Varying Results 70

(i) Significant Relationship 70

(ii) Insignificant Relationship 71

VI

(b) Mixed Results 72

(i) Relationship with Similar Strength but Varying Directions 72

(ii) Relationship with Varying Strengths and Directions 72

4.3.3 Stage Three: Elimination based on Added-Value to the Analysis 75

(a) Market Capitalisation (MC) 76

(b) Dividend per Share (DPS) Versus Dividend Yield (DY) 77

(c) Earnings per Share (EPS) Versus Price-Earnings Ratio (P/E Ratio) 77

(d) Money Supply 79

(e) Inflation Rate (IFR) 80

(f) Interest Rate (IR) 81

(g) Shariah-Compliance as a Firm-Specific Factor 82

4.4 Phase Two: Findings of Regression Analysis 84

4.5 Summary 96

Chapter Five: Discussions 97

5.1 Introduction 97

5.2 Positive Relationship between Market Capitalisation (MC) and M-REIT

Share Prices

97

5.3 Negative Relationship between Dividend Yield (DY) and M-REIT Share

Prices

99

5.4 Positive Relationship between Price-Earnings Ratio (P/E Ratio) and M-

REIT Share Prices

101

5.5 Positive Relationship between Interest Rate (IR) and M-REIT Share Prices 102

5.6 Negative Relationship between Inflation Rate (IFR) and M-REIT Share

Prices

103

5.7 Positive Relationship between Shariah-Compliance and M-REIT Share

Prices

104

5.8 Summary 106

Chapter Six: Conclusion, Contributions, Implications and Recommendations 107

6.1 Summary of Thesis 107

6.2 Summary of Results 109

VII

6.3 Contributions of the Study 111

6.3.1 Extension of Research on the Factors that Drive the Share Price

Movements of REITs in the Malaysian Context

111

6.4 Implications of the Study 113

6.4.1 Existing and Potential Investors: Reduction of Uncertainty 113

6.4.2 Standard Setters: Motivation to Enhance the Spread of Shariah-

Compliant REITs

113

6.4.3 Industry Development and Growth: Becoming More Attractive 114

6.5 Limitations and Recommendations 115

6.6 Conclusion 115

References

VIII

List of Tables

Page

Table 1: REITs Listed on Bursa Malaysia 9

Table 2: Previous Studies on the Factors that Drive the Movements of Share

Prices in General

21

Table 3: Previous Studies on the Factors that Drive the Movements of REIT

Share Prices

34

Table 4: Variable Selection Process and Outcome 83

Table 5: Regression Output of the Firm-specific Independent Variables 85

Table 6: Hypotheses (H1, H2 and H3) 86

Table 7: Results of the Hausman Test Run of the Regression Model of Firm-

specific Independent Variables

87

Table 8: Regression Output of the Macroeconomic Independent Variables 89

Table 9: Hypotheses (H4 and H5) 90

Table 10: Results of the Hausman Test Run of the Regression Model of the

Macroeconomic Independent Variables

91

Table 11: Regression Output of the Firm-specific Independent Variables

(including Shariah-Compliance)

92

Table 12: Hypotheses (H1, H2, H3 and H6) 93


Firm-Specific Independent Variables (including Shariah-

Compliance)

95

IX

List of Diagrams

Page

Diagram 1: Variable Selection Criteria 56

Diagram 2: Conceptual Framework 58

A Study of the Factors that Affect Share Price Movements of REITs in Malaysia by Wong Wen Yih Page 1

CHAPTER ONE INTRODUCTION

1.1 Background of the Study

A Real Estate Investment Trust (REIT) is an entity which owns or provides finance to income-

generating real estate (Realty Mogul 2017). A REIT is normally traded on primary stock

exchanges and is modelled after mutual funds, in which investors invest in portfolios of

diversified real estate assets, thus, offering consistent income streams, diversification, enviable

transparency, liquidity and long-term capital appreciation for investors of all backgrounds and

financial capabilities (REIT.com 2017).

The United States has the longest history of having a REIT industry, where REITs were created

as President Eisenhower signed into legislation the REIT Act in 1960 (REIT industry timeline

2017). This opened access for a contemporary income-generating method through real estate

investment, combining the opportunities and strengths of both real estate and share-based

investments (History of REITs 2017). REITs provided the advantages of commercial real estate

investment to all investors, which were, in comparison, formerly only accessible to the richest

in the population, facilitated by mega financial intermediaries (REIT industry timeline 2017).

Because of regulatory instability and restrictions, the REIT industry in the U.S. underwent

stagnant development for the first two decades from 1960. According to Wu (2011), only after

the Tax Reform Act of 1986, did the industry start to grow gradually, and later experienced an

unprecedented boom in initial public offerings (IPOs) during the nineties. The REIT industry

experienced an alarming downturn in 2007 as it was impacted by the Global Financial Crisis

(GFC) and it recovered gradually starting in 2009 (Wu 2011; Yuksel et al. 2017, p. 87).

Over the last 57 years, the industry has expanded around the globe to a $1.073 trillion equity

market capitalisation, constituting approximately $3 trillion in gross real estate assets as

investors responded to the opportunity gradually, not only in the U.S. but around the world

(REIT industry financial snapshot 2017). Other than the REIT industry in the U.S., Australian

REITs (A-REIT) (which were formerly known as Listed Property Trusts) is one of the fastest-

growing REIT markets internationally. The first debut of an Australian Listed Property Trust

(LPT) was in 1971. Similarly to the U.S., the LPT market in Australia struggled with

development and growth in the seventies and eighties because of a passive management


structure but began to experience significant growth in market capitalisation in the early

nineties (Chan, Erickson & Wang 2003; Glickman 2014). The dramatic rise of A-REITs in the

nineties was also precipitated by colossal overbuilding in the eighties, leading to a significant

fall in private market real estate values (Downs & Fellow 1999). Therefore, property owners

explored REITs, or public market property, to raise capital at a lower cost than the return that

they could attain from utilising the capital raised, to purchase commercial property at the

depressed private market prices (Glickman 2014). This is known as positive spread investing.

Such conditions led to an upsurge of REIT initial public offerings in the early and mid-nineties.

According to Downs and Fellow (1999), the success of U.S. and A-REITs attracted a

considerable number of European and Asian countries to launch their REITs and be involved

in the REIT bandwagon. There has been rapid growth in REITs, as an indirect real estate

investment vehicle, in several Asian countries. Japan has become the most prominent country

in the development of the REIT industry in the last five years (Kaur 2017). Japanese REITs

reached a market capitalisation of RM489 billion in 2017. On the contrary, Malaysia is still

considered as an emerging Asian REIT market (Lee, Hishamuddin & Lee 2006; Osmadi 2010;

Wu 2011; Kaur 2017).

Malaysia was the first country in Asia, after Australia, to introduce listed property trusts (LPTs),

which were named; property trust funds (PTFs), to encourage small investors to invest in the

local property sector. In 1989, Amanah Harta Tanah PNB debuted on Bursa Malaysia as the

first PTF in Malaysia, followed by Amanah Harta Tanah PNB 2 and the Arab Malaysian First

Property Trust. These three PTFs did not manage to garner much investor interest due to

restrictive rules and low growth (Osmadi 2010; Wong 2015). According to Newell, Ting and

Acheampong (2002, p. 111), Malaysia emulated the regulatory framework of Australian LPTs,

but for the benefit of its indigenous people (the bumiputras), rules were added to restrain

foreign ownership in Malaysian PTFs. The Malaysian Securities Commissions (SC) drafted

the guidelines on PTFs in 1991, which set out two fundamental requirements: the legal

requirements for the formation of a PTF in Malaysia; and the requirements for issuing, offering

or inviting any party to buy units in such a PTF. The guidelines were revised in 1995 and 2002

but the performance of Malaysian PTFs remained unfavourable.


Before the year 2005, only the subsidiaries of financial institutions could establish and manage

PTFs. The poor performance of PTFs was also attributable to the lack of prime, or quality, real

estate in their portfolios, restrictive borrowing conditions and the lengthy acquisition period.

These factors diminished investors’ interest in Malaysian PTFs (Osmadi 2010). Osmadi (2010)

claimed that to cease the below-par performance of PTFs, the Malaysian government decided

to make major amendments to the regulatory framework by transforming PTFs into a REIT

structure. This led to more flexible regulatory rules and enhanced tax transparency. The REITs

in Malaysia were structured to contain the following constituents – the deed, the assets of the

REIT, the trustee, the management entity and the unit holders (LHAG Advocates and Solicitors

2018).

With the SC’s approval in 2008, the foreign ownership level in a Malaysian REIT (M-REIT)

could be up to 70 per cent (which was previously fixed at 49 per cent) while the minimum

percentage of Bumiputra ownership became 30 per cent. The non-bumiputra and foreign

ownership cap were significantly relaxed which was a huge boost to the M-REIT industry (Wu

2011). Unlike the majority of REIT industries around the globe, M-REITs brought their

investors lucrative returns throughout the Global Financial Crisis (GFC) in 2008 and 2009

which was caused by the sub-prime mortgage crisis, while REIT prices, in general, hit rock

bottom (Phoo & Samsudin 2018, p.43). As of 2017, there were a total of 18 REITs listed on

Bursa Malaysia, with a total market capitalisation of RM38 billion and a total asset size of

RM49 billion (Kaur 2017). Lieu (2018) claimed that some of the most profitable REITs in

Malaysia included the Axis REIT which profited from office building and warehouse rental

and the YTL REIT which focused on hotel property. According to Lee (2014), Kaur (2017)

and Lieu (2018), Malaysian REITs hold high investment potential as direct investment in

property is becoming less attractive, due to skyrocketing prices, thus, there has been a shift of

potential investors into the REIT industry.

1.2 Differences between Equity and Mortgage REITs

In the 1960s, Real Estate Investment Trusts (REITs) were inaugurated to offer investment

opportunities in profitable real estate for small scale investors because REITs do not require

huge start-up investment. Previous studies have noted the attractiveness of REITs for small-

scale investors (Kerch 1993). Among the benefits of REITs include the ability to diversify

investment portfolios, provide steady and satisfactory dividends, liquidity, transparency and


longstanding strong performance. According to Nickolas (2015), the regulatory requirements

for an entity to qualify as a REIT include having more than 100 shareholders, distributing 90

per cent or more of the taxable income as dividends to its shareholders and being overseen by

a board of directors. REITs are commonly categorised as being either equity or mortgage

(Barnes 2015; Nickolas 2015).

An equity REIT acquires property in a wide range of real estate subsectors, followed by the

development of the property as part of the REIT’s portfolio (Nickolas 2015). Their services

have been extended to also include leasing, tenant services, the development and maintenance

of the physical property and the like. The primary income stream of an equity REIT is the rental

income from its property holdings which can scale from retail stores to condominiums to

shopping malls and hotels. An equity REIT can own a diversified portfolio or specialise in an

asset type or a real estate sector (The Motley Fool 2018).

In many aspects mortgage REITs operate in the same way as equity REITs. For instance, both

types of REITs can be traded publicly on a securities exchange or privately and are required to

distribute 90 per cent or more of their taxable income (The Motley Fool 2018). However,

instead of investing in physical real estate property, mortgage REITs build their portfolios

mainly through single home mortgages, and in some cases, commercial property mortgages or

indirect credit extensions by acquiring loans or mortgage-backed securities (REIT.com 2017).

In layman’s terms, the primary income stream of mortgage REITs is from lending money to

property owners or operators, via loans and mortgages, and profiting from the net interest

margin (the net of the interest income from the mortgage loans and the cost of funding them)

or by selling mortgage-backed securities (Foster 2018). Accepted derivative strategies, such as

vigorous hedging techniques and securitised mortgage investments are utilised by mortgage

REITs to stabilise, or control, their credit risk and the volatility of interest rates (REIT.com

2017).

According to Nickolas (2015) and The Motley Fool (2018), equity REITs are generally

preferred among investors because they are similar to investing in the stock of a publicly-traded

entity, and also due to the perception of investors, in general, that rental income is more stable

than mortgage interest income. Approximately 90 per cent of the market capitalisation of the

industry is attributable to equity REITs, while mortgage REITs account for the remaining 10


per cent (Barnes 2015; The Motley Fool 2018). There are also hybrid REITs which invest in

both physical property and mortgages and loans, but their market share is insignificant.

1.3 Types of Malaysian Real Estate Investment Trusts (M-REITs)

This section illustrates the types of REITs in Malaysia. There were 18 REITs listed on the stock

exchange in Malaysia, Bursa Malaysia, at the year-end of 2017 (Tan & Shankar 2019).

However, the KIP REIT was not included in the survey population of this research because it

was newly established when the research and analyses were carried out and, thus, information

on the REIT was very limited or unavailable. According to the Laerd Dissertation (2012), in a

situation where the list of the population is imperfect, the total population sample does not

compromise the capacity of the research to achieve analytical generalisation when the missing

data issue is minor. Table 1 summarises the details of the 17 REITs (except, the KIP REIT)

listed on Bursa Malaysia as of 2017. They were all classified as equity REITs, based on their

operations, among which, four were recognised as Islamic or Shariah-compliant REITs

(Securities Commission Malaysia 2017).

1.3.1 Non-Shariah Compliant M-REITs

In Malaysia, there were 13 non-Islamic, or conventional, REITs as of 2017, excluding the KIP

REIT. They are not mandated to adhere to the Sharia law issued by the Shariah Advisory

Council (SAC) of the Securities Commission to enhance the formation of an Islamic REIT.

According to the Securities Commission Malaysia (2012), the non-Islamic REITs listed on

Bursa Malaysia are regulated by the Securities Commission which sets out the requirements to

be observed by a regular REIT via The Guidelines on Real Estate Investment Trusts, issued

under section 377 of the Capital Markets and Services Act 2007 (CMSA). The establishment

of such a REIT is less time-consuming and stringent (Securities Commission Malaysia 2012).

1.3.2 Shariah Compliant M-REITs

The world’s debut Islamic REIT was launched in Malaysia as the Al-Aqar KPJ REIT (Ting &

Noor 2007; Islamic Markets 2018). An Islamic REIT’s key feature is that the activities or

operations, and wealth management practices carried out by the REIT must be compliant with

the Sharia law. For instance, the acquisition and accounting of the real estate property are

managed through Sukuk (Islamic bonds) and other Islamic financial instruments structured to

generate returns to investors without infringing any Islamic interests. A financial instrument is


considered legitimate, based on the Sharia law, if it adheres to three basic elements: 1) there

must not be any presence of riba or interest, and this implies that commodities, including money

that rises in value only by being lent to another party or vice-versa, is forbidden; 2) any

operation that gives rise to unethical concerns must be prohibited: alcohol, banks, gambling,

tobacco and pornography-related businesses are examples of unacceptable investments,

according to the Sharia law; and 3) the nature of the contract between the trading parties should

be valid and transparent, as clear guidelines are provided (Islamic Markets 2018). Also, if the

REIT has a mixture of Shariah and non-Shariah compliant operations, the percentage of income

derived from non-permissible operations to the Shariah-compliant REIT’s total revenue must

not be in excess of 20 per cent (Ting & Noor 2007; Malaysia International Islamic Financial

Centre (MIFC) 2013; Nordin 2018).

According to the Malaysia International Islamic Financial Centre (MIFC) (2013), guidelines

for Islamic REITs were issued by Malaysia’s Shariah Advisory Council (SAC) of the Securities

Commission in 2005 to pave way for Malaysia to be the pioneer of Islamic REITs. The issuance

of the guidelines was followed by the launch of the Al-Aqar KPJ REIT, the world’s first Islamic

listed REIT in 2006 (Ting & Noor 2007; Nordin 2018). In 2007 and 2008 respectively, the Al-

Hadharah Boustead REIT and the Axis REIT (the world debut of an Islamic industrial or office

REIT) were both listed on Bursa Malaysia as the second and third Malaysian Islamic REITs.

However, The Star Online (2013) reported that the Al-Hadharah Boustead REIT, the first and

sole Islamic plantation REIT was privatised in 2014 while the Axis REIT was first established

in 2005 and subsequently relisted as an Islamic REIT in December 2008. The Securities

Commission of Malaysia (2012) stated that at the end of 2008, all of the Islamic REITs listed

on Bursa Malaysia were reclassified as Shariah-compliant REITs following the guidelines

redrafted by the SAC. In 2013, the inauguration of the KLCC REIT took place and Malaysia

was again the pioneer of a Shariah-compliant stapled REIT. According to the Malaysia

International Islamic Financial Centre (MIFC) (2013), a stapled REIT is an investment vehicle

that comprises more than one individual organisation that trades through a single financial

instrument. The KLCC REIT’s portfolio included three primary assets which were; the

Petronas Twin Towers, Menara ExxonMobil and Menara 3 Petronas. Subsequently in 2015,

the Al-Salam REIT was established to primarily focus on investing in Shariah-compliant

property (Malaysia International Islamic Financial Centre (MIFC) 2013, Islamic Markets

2018). Therefore, as of 2017, there were four Shariah-compliant REITs listed on Bursa


Malaysia which were; the Al-Aqar KPJ REIT, Axis REIT, KLCC REIT and the Al-Salam

REIT.

Based on a statement made by the Malaysia International Islamic Financial Centre (MIFC)

(2013), the principal challenge of the international spread and growth of Shariah-compliant

REITs is the inadequacy of a distinct regulatory framework and standards that can facilitate the

governance of their operations. Emulating Malaysia’s pioneering experience in the Shariah-

compliance of its REITs, various countries, such as Kuwait, Bahrain and Singapore ventured

into Shariah-compliant REITs in following years. In 2010, Singapore launched its first Shariah-

compliant REIT, the Sabana REIT, which later became the largest Shariah-compliant REIT in

the world, as its real estate property value expanded to SGD 1.22 billion in 2013 (Islamic

Markets 2018). Although Indonesia has the most substantial Muslim population in the world,

no Shariah-compliant REIT had been listed on its stock exchange until 2012. According to

Sintarini (2017, p. 166), even conventional REITs were barely known as alternative financial

instruments in the Indonesian community. After the launch of its first REIT in 2012, namely;

Ciptadana Properti Ritel Indonesia, this REIT remained the only REIT in the Indonesian market.

Therefore, the author expressed that the challenges facing the market sector in introducing

Shariah-compliant REITs were expected to be prevalent. Indonesia’s tax rate is claimed to be

one of the major hindrances as well (Sintarini 2017, p. 172).

In comparison, Malaysia offers more clear-cut rules and regulations to enhance the

development of Shariah-compliant REITs and ensures that all of its REITs are overseen by

several levels of stakeholders including; the unit holders, REIT managers, trustees, regulatory

authorities and the Shariah Advisory Committee (SAC) (Islamic Markets 2018). They are

under the purview of both the Securities Commission of Malaysia and Bursa Malaysia.

According to the Malaysia International Islamic Financial Centre (MIFC) (2013), the capacity

of Shariah-compliant REITs to grow and expand globally is expected to increase. The main

reason behind their potential to thrive, as an international wealth management investment

vehicle, is because their structure is established upon tangible real assets. Aquila Capital (2014)

and Watt (2015) also stated that real assets can offer relatively greater stability to investors in

a range of market climates because the investments are connected to the real economy.

Moreover, the authors claimed that Muslim investors and institutions are more prone to

investing in real tangible assets due to their compatibility with Sharia finance principles that


promote a connection between the financial sector and the real economy. The success of the

Malaysian and Singaporean Shariah-compliant REITs have enhanced confidence that Shariah-

compliant REITs have favourable prospects to evolve into lucrative real estate investment

products around the globe (Malaysia International Islamic Financial Centre (MIFC) 2013).

While the adverse impacts of the GFC were apparent in the world’s economies, Shariah-

compliant REITs in Malaysia proved to be more defensive against volatility and shocks than

the conventional M-REITs, as well as the other conventional and Islamic REIT markets

internationally (Newell & Osmadi 2009, p. 329).

To offer clarity to both institutions and investors who have an interest in operating Shariah-

compliant REITs, Malaysia has established distinct and comprehensive regulatory standards

and a framework relevant to Shariah-compliance within the sector through the SAC (Malaysia

International Islamic Financial Centre (MIFC) 2013). Furthermore, according to the Securities

Commission Malaysia (2012), the fact that a 70 per cent foreign shareholding is allowed in

Malaysian shariah-compliant REITs, along with the non-existent limitation on locally

domiciled Shariah-compliant REITs to procure foreign assets, have increased the flexibility for

foreign REIT managers, or investors, to make Bursa Malaysia a realisable avenue to list REITs,

as well as Shariah-compliant REITs. Therefore, the Malaysia International Islamic Financial

Centre (MIFC) (2013) and Foo and Muhammad (2015) stated that Shariah-compliant M-REITs

are perceived to have the potential to perform more lucratively in the future. Also, Shariah-

compliant M-REITs are claimed to play a vital role at strengthening the competitiveness of the

country’s Islamic financial instruments by attracting Muslim investors to channel their focus

and investment into Shariah-compliant assets and funds (Ting & Noor 2007; Ahmad Tajjudin

Rozman et al. 2015, p. 7).

Table 1 shows the list of REITs listed on Bursa Malaysia, and whether they are non-Shariah

compliant or Shariah-compliant REITs.


Table 1: REITs Listed on Bursa Malaysia

Name Category Islamic/ Shariah Compliant

1. Amanah Harta Tanah PNB Equity

2. Al-`Aqar Healthcare REIT Equity ✓

3. Al-Salam Real Estate Investment Trust Equity ✓

4. AmFirst Real Estate Investment Trust Equity

5. AmanahRaya Real Estate Investment Trust Equity

6. Atrium Real Estate Investment Trust Equity

7. Axis Real Estate Investment Trust Equity ✓

8. Capitaland Malaysia Mall Trust Equity

9. Hektar Real Estate Investment Trust Equity

10. IGB Real Estate Investment Trust Equity

11. KLCC Property Holdings Berhad Equity ✓

12. MRCB-Quill REIT Equity

13. Pavilion Real Estate Investment Trust Equity

14. Sunway Real Estate Investment Trust Equity

15. Tower Real Estate Investment Trust Equity

16. UOA Real Estate Investment Trust Equity

17. YTL Hospitality REIT Equity


In the next section, the problem statement of the research, which describes the existing issues

related to the topic that need to be addressed and forms the context of the study, is discussed.

1.4 Problem Statement

Asian Real Estate Investment Trust (REIT) markets, in spite of being in existence for merely a

decade, have become substantially robust, and this is mainly attributed to an upsurge in the

number of Initial Public Offerings (IPOs) of Asian REITs (Kaur 2017). Some REIT markets in

Asia, for example, Japan and Singapore, have been successfully established and have

outperformed those in many other countries. According to Osmadi (2010), Wong (2014) and

Ernst & Young Global Limited (2016), Malaysia is one of the emerging REIT markets and

provides significant investment opportunities.

However, Kaur (2017) stated that in comparison, the performance of Malaysian REITs (M-

REITs) has been weaker (slightly under par compared to Asian REITs’ average returns) and

their market capitalisation of RM38 billion is still trifling as compared to Japan, Singapore or

Australia. According to the author, this is because most investors and analysts have a neutral

outlook for M-REITs, due to the lack of analysis and known near-term catalysts of their share

price fluctuations. Past studies on the factors affecting share price movements of M-REITs are

limited and they have focused primarily on a few potential firm-specific variables, such as

market capitalisation, dividend yield and net asset value (NAV). Also, the interest rate and

inflation rate are the only macroeconomic factors whose relationships with the movements of

M-REIT share prices have been analysed (Kelly & Thomas 2016, p. 130-131). Without

examining other potential variables or justifying the selection of the variables, may not suffice

to establish the reliability and validity of the research. To have a holistic perspective of the

drivers of M-REITs’ share price movements and their impacts, it is imperative to analyse both

potential firm-specific and macroeconomic factors. According to Case (2016), the performance

of REITs is driven not only by firm-specific issues but also by the macroeconomic environment.

Kaur (2017) stated that Asian REIT markets are expected to account for 35 per cent of the

world’s REIT markets by 2020, as compared to the current 25 per cent. Therefore, for M-REITs

to gain opportunities in the growing REIT markets in Asia, it is crucial to minimise the

knowledge gap, as intended by the research.


Furthermore, Wu (2011) asserted that the uncertainty of investors, both foreign and local, in

the catalysts of M-REITs’ share price movements is seen as an investment deterrent. It implies

that both existing and potential investors are not well informed of the logical expectations

regarding the stocks and are, thus, deprived of behaving rationally. Also, Gilo (2013) claimed

that investors’ confidence is negatively influenced when their knowledge of the catalysts of

share price movements is lacking. It is more likely for investors to refrain from investing in

shares during such a high level of uncertainty. This is supported by Ung (2012) and Rao (2019),

who stated that Malaysian REIT investors are generally more prone to risk and uncertainty

avoidance. Also, Duasa and Yusof (2013, p. 3) agreed that Malaysian investors are

conservative, which denotes that they have a low level of risk tolerance. They also found that

Malay investors have a higher level of risk avoidance than the Chinese, which may have some

impact on the prospects of Shariah-compliant REITs in Malaysia (Duasa & Yusof 2013, p. 14).

According to Hamid (2007), who studied the correlation between uncertainties and investment

decisions, uncertainties are positively and significantly correlated to delayed investment

decisions in Malaysia. Therefore, it is crucial to research deeper into the factors that drive the

share price movements of M-REITs, as they majorly influence investors’ investment decisions

when they are uncertain about the factors.

To sum up, the future growth potential of Asian REIT markets is substantial, and for M-REITs

not to lose out on the opportunities, investor confidence in the industry has to be enhanced.

Without information or knowledge on what will shift the share prices of M-REITs, it is claimed

that both foreign and local investors are less willing to invest in them as compared to other

more established Asian REIT markets, such as the Japanese or Australian REIT markets,

because of the sense of uncertainty in M-REITs. Thus, the findings of the study are expected

to help investors identify both firm-specific and macro-level economic factors that drive the

share price movements of M-REITs. It is expected to reduce uncertainty, strengthen investor

confidence and enable the investors to make more informed decisions. This will, in turn, allow

M-REITs to attract more investors, seizing the opportunities offered in such a growing market

(Kaur 2017).


1.5 Research Aims and Objectives

The problem statement helps to build the focal point of the study and what the study intends to

accomplish. The study aims to investigate the firm-specific, as well as the macro-level

economic factors that drive the share price movements of Malaysian REITs (M-REITs). The

objectives include:

1. To identify the firm-specific factors which affect the share prices of M-REITs.

2. To identify the macroeconomic factors which affect the share prices of M-REITs.

3. To examine the relationship between each of the analysed factors and M-REIT share

prices.

4. To examine the effect of Shariah-compliance on M-REIT share prices.

1.6 Research Questions

The research questions are those questions that the study aims to answer, and they are generated

through the identification of the problem statement. The research questions of this study

include:

1. What are the firm-specific factors that affect the share prices of M-REITs?

2. What are the macroeconomic factors that affect the share prices of M-REITs?

3. What is the relationship between each of the factors analysed and M-REIT share prices?

4. What is the relationship between Shariah-compliance, as a firm-specific factor, and M-

REIT share prices?

1.7 Structure of the Thesis

The layout of the rest of this research paper is as follows. Chapter Two is the literature review

which not only summarises but also provides clarification on the limitations of the current state

of knowledge on a subject matter. It also builds the foundation of the conceptual framework,

providing the backbone for this research study. Chapter Three outlines the research

methodology which contains the research philosophy, research framework, variable selection

criteria, hypotheses, conceptual framework, data collection and data analysis. Subsequently,

Chapter Four contains the findings from both phases of the research, while Chapter Five

discusses the rationale behind the results found through data analysis. Finally, Chapter Six

concludes the paper by including the summary of the thesis and results, the contributions and


implications of this study together with the limitations of the study and recommendations for

future studies.

1.8 Summary

To sum up, Chapter One consists of a background of the study, the types of M-REITs, the

problem statement, research aims and objectives, research questions and the structure of the

thesis. The next chapter talks about the literature review.


CHAPTER TWO LITERATURE REVIEW

2.1 Introduction

This chapter gives an overview of the successful establishment and development of REIT

industries in various countries, past studies on the factors that drive share price movements, in

general, and in the REIT industry specifically and also the impacts of Shariah-compliance on

REITs. It synthesises the information in past studies and critically analyses the information

through the identification of current knowledge gaps and limitations of the past research. It

helps to develop areas for further studies and evaluate areas of controversy (Royal Literary

Fund 2018).

2.2 History and Prospects of the REIT Industry

This subsection outlines a more detailed history of the REIT industry in various countries. The

understanding of the history of REITs widens the frame of reference concerning the industry,

and yields insights into the development and prospects of REIT markets around the globe.

2.2.1 The United States

The establishment of the United States (U.S.) REITs took place through Congress in 1960 when

President Eisenhower signed into legislation, the REIT Act, which led to a new income-

generating investment vehicle (History of REITs 2017). REITs were created to have the most

fundamental and beneficial attributes of real estate investment property and share-based

investment. The advantages of commercial real estate investment were no longer offered to the

richest and largest financial intermediaries but to all individual investors (REIT industry

timeline 2017). According to History of REITs (2017), the establishment of U.S. REITs has

encouraged more than 35 countries around the globe to adopt the same model and to establish

this contemporary investment vehicle.

Over the first two decades, the growth and development of U.S. REITs were sluggish but the

Tax Reform Act of 1986 transformed the climate for the industry notably. In 1986, the U.S.

claimed to have experienced one of their most significant tax structure reformations, namely;

the Tax Reform Act of 1986. Through the Tax Reform Act, the tax code in the U.S. became

more comprehensible and restrictions on REITs were moderated (Kagan 2018; All Business


2019). Congress amended the licensing requirements of REITs and the taxation applied to them

was relaxed. According to Engle (2017), the Act implemented stringent restrictions on loss

deductions which caused the REIT industry in the U.S. to lose some of their tax perks. However,

it still provided the REIT industry with a relative edge as direct real estate investors experienced

a greater removal of their tax benefits (Xu & Yiu 2017, p. 12). After the tax reformation, the

industry began to grow and experienced an unprecedented boom in initial public offerings

(IPOs) in the nineties.

The REIT industry faced an alarming downturn in 2007, caused by the U.S. sub-prime

mortgage crisis (Wu 2011). Amadeo (2019) stated that deregulation in the U.S. financial

industry precipitated the crisis, as it allowed financial institutions to become involved in

strategic hedging through derivatives trading. The financial institutions in the U.S. then called

for more mortgages to buttress the remunerative sales of those derivatives. Thus, interest-only

loans were on the rise, which opened access to loans for borrowers with poor credit rating, the

sub-prime borrowers. According to the author, it eventually resulted in an unnerving default

rate when prices of the direct real estate investment began to fall. There was an oversupply of

houses and the trapped sub-prime homeowners could not afford to pay the mortgages. The

bursting of the sub-prime bubble led to the outbreak of the 2008 Global Financial Crisis (GFC).

The REIT industry was majorly, and negatively, affected by the GFC together with the stock

markets but recovered gradually in 2009 (Wu 2011; Yuksel et al. 2017, p. 87).

Over the years, investors have grabbed hold of the opportunities offered by the industry and,

therefore, after almost six decades, the U.S. REITs have expanded to a $1 trillion equity market

capitalisation which is equivalent to $3 trillion in gross real estate assets (History of REITs

2017). However, $1 trillion of those were attributed to privatised REITs. The public-listed U.S.

REITs consisted of a portfolio of 500,000 real estate properties, as of 2017. Also, the industry

supported 2.3 million full-time workers who benefited from $140.4 billion in salaries in the

U.S. (Economic contribution of REITs in the United States 2017). The favourable prospects

caused the industry to be the first recognised in a new headline sector under the classification

of the Global Industry Classification Standard in 2016. According to Mathrani (2018), the

industry was expected to continue to grow in market capitalisation, diversity, adaptability and

geographical reach.


2.2.2 Australia

Australia was the fourth country in the world to introduce REITs into the market, after the U.S.,

the Netherlands and New Zealand. Australian REITs (A-REITs) were established in 1971 when

the first listed property trust (LPT), the General Property Trust (currently known as the GPT

Group), was listed on the Australian Stock Exchange. Australian LPTs were perceived to be a

good alternative over direct property investing and a lower-risk investment which provided

stability by generating income through rental. Subsequently, the development and growth of

the industry took place which included offshore investments and financial engineering (The

Australian Investors Association 2012).

According to Chan, Erickson and Wang (2003) and Glickman (2014), similarly to the U.S.

REIT industry, the LPTs had challenges developing and expanding during the seventies and

eighties, due to their passive and overly simplified management structure. Nevertheless, the

authors stated that they started to experience noteworthy growth in market capitalisation in the

early nineties. This growth was sparked by colossal overbuilding in the eighties, leading to a

significant fall in private market real estate values (Downs & Fellow 1999). According to the

authors, this further propelled the regulatory suppression on banks and insurance companies

on savings and loan lending, leading to a credit crunch in commercial property markets.

Regulators had to prevent conventional real estate lenders from lending more credit to real

estate owners and developers, causing numerous defaults and bankruptcies among them.

Osmadi (2010) stated that it was during this same period that the stock markets experienced

unprecedented share price rises, creating significant variations in real estate values in the public

and private markets. Thus, LPTs began to rise as an alternative for property owners. They

intended to raise capital at a lower cost than the return they could gain from utilising the capital

raised to participate in direct property investing at the depressed private property market prices

(Glickman 2014). The positive spread investing was followed by an upsurge of LPT initial

public offerings in the early and mid-nineties. The LPTs evolved into REITs only in March

2008. Despite the successes of A-REITs, 2017 was a gloomy year for the industry. The A-

REITs had a negative total return of 6.3 per cent due to a high level of uncertainty in the

industry. The fact that a few of the Australian international brands failed to survive and the

lagged arrival of Amazon triggered the rise of uncertainty among the real estate and REIT

investors (BDO Australia 2017).


2.2.3 Japan

The successes of the U.S. and Australian REITs attracted many Asian countries to venture into

the REIT industry and to join the REIT bandwagon. There has been a rapid growth of REITs

as an indirect real estate investment vehicle in a considerable number of Asian countries, and

Japan was one of them (Downs & Fellow 1999).

The inauguration of Japanese REITs (J-REITs) took place in 2000 when the Investment Trust

Act was amended to accommodate the structure of J-REITs (Seki 2013). It allowed both

investment trusts and investment corporations to operate, and, since then, all of the J-REITs

have been modelled as investment corporations (adopting an external or passive management

structure). Under such a structure, J-REITs have benefited from low and limited business risks

(The Association for Real Estate Securitization n.d.). The industry began to bloom after the

debut of the first two J-REITs on the Tokyo Stock Exchange (TSE) in 2001, by the two most

prominent real estate companies in Japan. In 2007, the J-REIT industry encountered an

alarming downturn, caused by the impacts of the GFC and subsequently further dampened by

the Great East Japan Earthquake in 2011 (The Association for Real Estate Securitization n.d.).

The J-REIT industry gradually recuperated in 2012 and as of 2016, there were 57 J-REITs

listed on the TSE with a market capitalisation of approximately $104 billion, the second-largest

REIT industry internationally after the U.S. REITs. The growth of the J-REIT industry was

majorly caused by the complementary policies introduced by the Bank of Japan, for example,

negative interest rates and the government’s mandatory REIT asset allocation (Guan 2017).

Kaur (2017) agreed that Japan had become the most prominent country in the development of

the REIT industry in the last five years. J-REITs reached a market capitalisation of RM489

billion in 2017.

2.2.4 Singapore

In 2001, the first Singapore REIT (S-REIT), SingMall Property Trust, which was operated by

Capitaland, failed at its launch and listing on the Straits Times Index (SGX: ^STI) as the

subscription of shares merely reached 80 per cent of the issuance level. According to

Kolesnikov (2011), the failure was triggered by poor market sentiment and a high level of

uncertainty surrounding what a REIT was, and the factors driving its return and performance.

Nevertheless, the SingMall Property Trust was successfully launched and listed in 2002 and

remained as the only REIT listed on the STI until 2014, even though there were 28 S-REITs


listed on the SGX. The S-REIT 20 Index was introduced in 2015, and as of 2017, there were

32 S-REITs listed on the Singapore Exchange (SGX) with a market capitalisation of

approximately $72 billion (SGX My Gateway 2017). According to Dayani (2018), the

performance of S-REITs in 2017 was outstanding and the SGX S-REIT 20 Index achieved a

notable return of approximately 27 per cent. Although S-REITs were not expected to deliver

such exceptional returns in the following year, their prospects remained favourable. The

outlook of Asian REITs was positive and S-REITs were expected to grab hold of the

opportunities offered by the industry and become an international REIT hub (REITAS 2018).

In fact, according to REITAS (2018), the number of S-REITs grew to 42 with a market

capitalisation of $90 billion in 2018, making up eight per cent of the market capitalisation of

all of the entities listed on the SGX.

2.2.5 Malaysia

The history and prospects of Malaysian REITs (M-REITs) have been discussed in detail in

Para 1.1 Background of the Study. Emulating the example set by Australia, Malaysia

introduced property trust funds (PTFs) which were modelled after the Australian LPT in 1989.

The first three Malaysian PTFs failed to garner much investor interest due to the perceived low

growth of the industry and the restrictive rules set by the Securities Commission of Malaysia

to offer privileges to the indigenous people (Newell, Ting & Acheampong 2002, p. 111).

According to Osmadi (2010), the fact that only the subsidiaries of financial institutions could

launch and manage PTFs, the lack of prime and diversified property in their portfolios,

stringent borrowing requirements and time-consuming acquisitions were all reasons behind the

failure of PTFs. The Malaysian government amended the regulatory framework by

transforming the PTFs into a REIT structure so that the below-par performance could improve

(Osmadi 2010). Furthermore, Wu (2011) stated that the permissible level of foreign ownership

in an M-REIT rose to 70 per cent which helped to attract more investors. As of 2017, there

were a total of 18 REITs listed on Bursa Malaysia, with a total market capitalisation of RM38

billion and a total asset size of approximately RM49 billion (Kaur 2017). The U.S. REIT

market remained as the largest REIT market internationally while J-REITs and A-REITs

remained as the second and third largest REIT markets (REITAS 2018).


Even the S-REIT industry, which was inaugurated much later than that of M-REITs, achieved

around a $72 billion market capitalisation in 2017, whereas, M-REITs combined merely had a

market capitalisation of approximately $10 billion or RM38 billion in 2017. However, unlike

the majority of the REIT industries around the globe, M-REITs still performed favourably and

provided lucrative investment returns during the GFC in 2008 and 2009, caused by the sub-

prime mortgage crisis, while most REITs in the world were dampened greatly (Phoo &

Samsudin 2018, p.43). The authors agreed that the potential of M-REITs had been underrated

but the industry was moving in a favourable direction toward maturity due to the e-commerce

and big data trends. This was rebutted by Ng (2016) who claimed that the climate for the REIT

industry in Malaysia was expected to be gloomy over the next few years because the M-REIT

Managers Association had gauged an oversupply in the real estate property market. He further

expressed that this situation would negatively affect the profits of M-REITs and their dividend

distributions, and cause poor growth in the M-REIT industry. Thus, a REIT index was

introduced in October 2017 to seize the distinctive market segment which represented all of

the entities in the M-REIT industry, regardless of the asset types that the index constituents

were specialised in (Kumar 2018). According to Kumar (2018), the index was claimed to be a

good cushion against the prevailing climate in terms of their growth and performance because

as an index, adjustment was unnecessary for dividends distributed and dividends were paid per

share instead of the minimum 90 per cent of taxable income that REITs were required to pay

to their shareholders. In comparison with Australia, Japan or Singapore, Malaysia was still

considered as an emerging Asian REIT market where it possessed great potential to be a hub

for REIT investment, be it REITs, in general, or the Shariah-compliant REIT market (Lee,

Hishamuddin & Lee 2006; Osmadi 2010; Wu 2011; Kaur 2017). According to Atchison and

Yeung (2014), if the M-REIT industry were to maximise its potential, it could impact the

economy significantly, especially, in terms of job creation and GDP growth.

To sum up, some of the common issues faced by the REIT industries in various countries

include; the challenge to garner investor interest and confidence, especially, when they were

first established, the restrictions on their structure and ownership, the high dividend

distributions required, which could be a burden when the business climate is unfavourable, and

the deterioration of their performance during the 2008 GFC or unexpected external shocks.

However, both the conventional and Shariah-compliant M-REITs behaved resiliently in the

face of the GFC, although M-REITs, in general, were still perceived as an emerging REIT


market, as compared to the REIT markets in the U.S., Australia, Japan and Singapore (Wu

2011; Kaur 2017). This suggests that REITs may react unconventionally compared to

organisations, in general, which may be due to their unique structure, and their performance

and returns could be driven by different factors based on their geographical position. Therefore,

it is vital to identify the factors that drive share prices to make better predictions on whether a

REIT would be a good or bad investment.

2.3 Factors that Drive the Movements of Share Prices in General

The share price movement of a company’s stock is a crucial indicator giving a vivid view of

market expectations of its performance, and at what price existing and potential investors are

willing to buy or sell shares in the company, thus, affecting investor confidence in its prospects

(Zacks Investment Research 2017; Rappaport 2017). According to Gilo (2013) and Profit by

knowing why stock prices are volatile (2017), investor’s confidence is adversely impacted by

their lack of knowledge about the factors causing the share price to move, and they are more

likely to refrain from investing in the shares during such high level of uncertainty. According

to Ung (2012) and Rao (2019), Malaysian REIT investors generally have less tolerance for

both risk and uncertainty, which indicates that they are prone to avoid risk and uncertainty.

This is crucial, as it majorly influences their investment decisions when they are uncertain

about the factors that drive share price movements.

Due to its profound effects on a company, a considerable number of studies have attempted to

identify the major factors behind fluctuating share prices, analysing different stock exchanges

or industries. The literature review will look into the factors that drive share price movements

in general, followed by the factors that affect REIT share prices.

Table 2 shows information regarding previous studies conducted on the factors affecting the

movements of share prices in general.


Table 2: Previous Studies on the Factors that Drive the Movements of Share Prices in

General

No Researchers Independent Variables Analysed

Year Market Firm-Specific Macroeconomic

1 Khan

Dividend Yield (DY) (+),

Retained Earnings

(RE) (Insignificant),

Price-Earnings Ratio

(P/E Ratio) (Insignificant)

2009 Bangladesh

2 Allahawiah

and Amro Market Capitalisation (+) 2012 Jordan

3

Malhotra,

Chandiwala

and Tandon

Book Value (BV)/

Net Asset Value (NAV) (+),

Earnings per Share

(EPS) (+),

Dividend per Share

(DPS) (Insignificant),

Dividend Payout Ratio

(DPR) (Insignificant),

DY (-), P/E ratio (+)

2013 India

4 Geetha and

Swaaminathan

BV (+),

EPS (+),

DPS (Insignificant),

P/E ratio (+)

2015 India


5 Sharif, Purohit

and Pillai

BV (+),

EPS (Insignificant),

DPS (+),

DY (-),

P/E ratio (+),

Return on Equity

(ROE) (+),

Debt to Asset Ratio

(D/A Ratio) (-),

Market Capitalisation (+)

2015 Bahrain

6 Salam, Islam

and Hasan EPS (+) 2015 Bangladesh

7 Kodithuwakku

EPS (+),

DPS (+),

NAV (+)

2016 Sri Lanka

8 Aveh and

Vitor

BV (+),

EPS (+),

Market Capitalisation (+),

ROE (+),

DY (-)

2017 Ghana

9 Avdalovic

BV (+),

Return on Assets

(ROA) (+),


2018 Serbia


10 Nautiyal and

Kavidayal

EPS (Insignificant),

Economic Value Added

(EVA) (+),

DPS (-),

2018 India

11 Adam and

Tweneboah

Interest Rate (IR) (-),

Inflation Rate (IFR)

(Insignificant),

Exchange Rate (ER)

(-)

2008 Ghana

12 Aroni

IR (-),

IFR (Insignificant),

ER (-),

Money Supply

(Insignificant)

2011 Kenya

13 Naik and Padhi IFR (-),

Money Supply (+) 2012 India

14 Khan and

Zaman


Money Supply

(Insignificant)

2012 Pakistan

15 Heng et al.

IR (-),

Money Supply (+),

IFR (-),

Crude Oil Price

(Insignificant)

2012 Malaysia

16 Sirucek Money Supply (-) 2012 USA


17 Barasa

Money Supply

(Insignificant),


Gross Domestic

Products (GDP)

(Insignificant)

2014 Kenya

18 Hussein IFR (-) 2017 Uganda

19 Singh

EPS (+),

Leverage (represented by

the Debt to Capital ratio)

(+),

First Lag of the Share Price

(+),

DPR (Insignificant),

P/E Ratio (Insignificant),

Size (represented by the

logarithms of total assets)

(Insignificant)

IFR (-),

GDP (Insignificant) 2018 Oman

2.3.1 Firm-Specific Factors

Firm-specific factors are factors related to the organisation or individual units of an economy,

rather than the aggregate economic conditions (Madura 2011, p. 118; Chandrapala &

Knapkova 2013, p. 2183). Khan (2009), Allahawiah and Amro (2012, pp. 236-245), Malhotra,

Chandiwala and Tandon (2013, pp. 86-95), Geetha and Swaaminathan (2015, pp. 97-109),

Sharif, Purohit and Pillai (2015, pp. 207-216), Kodithuwakku (2016, pp. 67-76), Salam, Islam

and Hasan (2015, pp. 15-33), Aveh and Vitor (2017), Avdalovic (2018, pp. 7-20), Nautiyal and

Kavidayal (2018, pp. 707-721) and Singh (2018) investigated the relationships between

independent variables, such as book value (BV), earnings per share (EPS), retained earnings

(RE), market capitalisation (MC), return on equity (ROE), return on assets (ROA), leverage


(represented by the debt to capital ratio), first lag of the share price, debt to asset ratio (D/A

Ratio), size (represented by the logarithms of total assets), economic value added (EVA),

dividend yield (DY), dividend per share (DPS), dividend payout ratio (DPR), price-earnings

ratio (P/E ratio, which is the market price of a company’s equity share divided by the EPS) and

the share price (dependent variable). According to Averkamp (2017), book value is defined as

the value at which an asset is carried on the statement of financial position and calculated by

taking the cost of a company’s total assets net of its total liabilities. Net asset value (NAV), an

alternative term used, instead of book value, is more commonly seen in the records of property

firms and equity holdings, including real estate investment trusts, where potential and actual

price appreciation of real estate assets are considered in the determination of NAV (Maverick

2018).

Geetha and Swaaminathan (2015, p. 109) found through their analysis that as the BV, EPS or

P/E ratio of a company rose, its share price appreciated as well while the DPS did not affect

the share price movement. The authors conducted a comparative analysis between the

automobile and information technology industries but did not find any significant difference

between the impacts of the factors on the share prices. According to the authors, they focused

their analysis on a sample of four companies from the automobile and IT industries in India,

which were listed on the National Stock Exchange (NSE) and the Bombay Stock Exchange

(BSE). Their data collection was carried out from the year 2010-2014 (five years, a short

sample period). By including only a few companies of the two industries, the distribution was

likely skewed (Mordkoff 2016). Moreover, the companies analysed were self-selected and self-

selection sampling is deemed to be biased (Lavrakas 2008; Leng & Zhang 2013). According

to Button et al. (2013, p. 366) and Deziel (2017), a short sample period, of only a few years.

and a small sample size decrease any research’s statistical power and this would reduce its

probability to reflect a true or reliable result. Geetha and Swaaminathan (2015, p. 109) also

stated that further studies should be extended by including a larger sample size. The sample

size used by them could not represent the aggregate result of the share price movements of

India’s listed entities and had, thus, restricted the generalisability of the findings. Similarly,

Kodithuwakku (2016, p. 67) collected five-years of data about 20 manufacturing companies

listed on the Colombo Stock Exchange (CSE) in Sri Lanka. The analysis was conducted by

adopting Pearson’s Correlation and Multiple Regression Model and the findings showed that a


company’s share price was favourably affected by its EPS, DPS and NAV. However, the author

did not make any prediction or explanation concerning the possible reasons for such findings.

Besides, Avdalovic (2018, p. 7) founded its study by analysing 95 per cent of the financial and

insurance organisations listed on the Belgrade Stock Exchange in Serbia. The data collection

was conducted from 2008 to 2014. The result drawn from the seven-years of data conveyed

that BV, market capitalisation (MC) and return on assets (ROA) could affect an organisation’s

share price positively and significantly (Avdalovic 2018, p. 19). The ROA is a profitability

ratio which quantifies the net income an organisation generates from its total assets (Grant 2018;

Kennon 2018). No possible reasoning was provided for the research findings. The results were

found by adopting multiple regression analysis and cluster analysis. Cluster analysis, also

referred to as segmentation analysis, is a statistical instrument which groups a set of data objects

into clusters of similar objects (Statistics Solutions 2019). It is an unsupervised statistical

technique where the drawbacks encompass vaguely established guidelines and the difficulty in

deciding on a suitable number of clusters. Furthermore, according to Avdalovic (2018, p. 19),

extended research should be carried out because only firm-specific factors were taken into

account. The author added that the usefulness and reliability of the findings were questionable

because the impacts of macroeconomic factors were excluded.

Similarly, Aveh and Vitor (2017) collected seven-years of data from 2008 to 2014 on all of the

organisations listed on the Ghana Stock Exchange, after its adoption of International Financial

Reporting Standards (IFRS). The ordinary least squares (OLS) method of panel data analysis

was adopted to investigate the determinants of share price movements in Ghana. The results

indicated that an organisation’s BV, EPS, MC and ROE had significant and positive

relationships with its share price movements, while dividend yield (DY) was found to be

significantly but negatively correlated with share price movements. However, the authors

claimed that only the four variables showing positive and significant correlations with the share

price should be taken into consideration, and the impacts of DY on share prices could be

disregarded only because the correlation was negative. They did not explain such a statement,

but it was highly disputable because a significant correlation stipulated the need to explore the

consequential effects of the predictor variable, regardless of the direction of its relationship

with the dependent variable (Guglielmi 2001).


Besides, an earlier research paper published by Malhotra, Chandiwala and Tandon (2013, p.

94) supported that BV, EPS and the P/E Ratio had positive relationships with the movements

of the share price. According to the authors, investors were generally concerned about the

actual value of the company or their investment and the profits earned by the company which

in turn reflected the possible returns of their investment. The research also concluded that a

company’s share price was not affected by its DPS and DPR, while DY had an inverse

relationship with share price movements. A simple linear regression model was adopted for the

research, but the possible reasons for such results remained unexplained. A sample of 95

companies was selected from the NSE for the period 2007 to 2012, encompassing various

sectors in India (Malhotra, Chandiwala & Tandon 2013, p. 86). Dissimilar from many other

past studies, Nautiyal and Kavidayal (2018, p. 707) deduced that EPS had no significant impact

on the share price movements of a company, while economic value added (EVA) and DPS

could affect share prices significantly. The relationship between EVA and share price

movements was positive, whereas, for DPS, a negative relationship was found, in line with

most past studies reviewed. The authors also asserted that the impacts of DPS were less

substantial than EVA, but still significant. The research adopted panel data analysis and

collected secondary data on 30 actively trading organisations listed on Nifty 50 Index of India

over a 20-year sample period, from 1995-2014. However, by examining only a few firm-

specific factors, the findings could not give a holistic view of the determinants of share price

movements.

The findings of Malhotra, Chandiwala and Tandon (2013, p. 94) on the impacts of dividend

yield (DY) on share prices of 95 companies listed on India’s stock exchange were contrary to

the discovery of Khan (2009) which stated that DY had a stronger positive relationship with

the share price as compared to retained earnings (RE). According to Khan (2009), both of these

variables explained the share price movements better than the P/E ratio, but the possible reasons

for such findings were not revealed. Khan (2009) stated that the limitations of his paper were

attributable to the high level of manipulation, anomalies and untruthful representation,

concerning the processing and preservation of the data and information needed by analysts and

investors, as Bangladesh (Dhaka Stock Exchange) was a newly emerging market.


Moreover, Sharif, Purohit and Pillai (2015, p. 207) founded their study on 41 companies listed

on the Bahrain Stock Exchange over a five-year sample period. The research methodology used

was panel data analysis. Other than demonstrating significant conformity with the results of

the abovementioned research that BV and the P/E ratio were positively related to share price

movements, the authors deduced that the DPS, MC and the ROE also had positive effects on

the share prices. Contrarily, the DY was negatively related to the share price and a high

significance level was identified through the analysis. Contrary to other research, EPS was

concluded to be inversely related to share price but insignificantly. Sharif, Purohit and Pillai

(2015, p. 213) claimed that Bahraini investors did not make their investment decisions based

on the EPS because they identified that the EPS rose, not only when a firm had a stronger profit,

but when stock repurchases were high. They also investigated the association of the debt to

asset ratio (D/A ratio) with the share price and concluded that they were negatively and

significantly related. This was because leverage would lead to a higher probability of

insolvency in the future.

Differently from the studies discussed above, Allahawiah and Amro (2012, pp. 238-239)

collected first-hand data by carrying out a questionnaire survey among a random sample

consisting of; senior management teams, financial brokers, lower-level managers and portfolio

managers in various fields. The respondents were gathered from 60 companies selected as a

random sample among the 227 companies listed on the Amman (Jordan) Stock Exchange.

Their findings showed that a company’s dividend policy, management quality, financial

position or health, in general, and size (Market Capitalisation) were positively related to its

share price movements. Similarly, even though Salam, Islam and Hasan (2015, p. 15) attempted

to identify the major factors that drive share price fluctuations among the 17 variables selected,

only EPS was analysed based on actual numerical data, and their analysis concluded that the

EPS' correlation with share price was significantly positive. The findings on the remaining 16

variables, such as the P/E ratio, industry performance and the DPS were reached by distributing

questionnaires to 30 respondents from different companies. It was believed that experts in the

field had a better insight into the drivers of share price movements (Allahawiah & Amro 2012,

p. 239). However, according to the authors, the sampling was narrow and the validity and

reliability of such data were restrained as the research was founded mainly on personal opinions.

This may reflect inherent bias in the participants’ traits (Laerd Dissertation 2012). Moreover,


sample selection bias could have occurred as only approximately 30 per cent of the larger

population was included in the sample, leading to a skewed representation of the full population.

Other than what has been discussed above, the common limitation of all of the past studies

mentioned is the exclusion of macro-economic factors, such as the inflation rate (IFR), the

gross domestic product (GDP) and the interest rate (IR).

On the contrary, Singh (2018) carried out an analysis of the impacts of both firm-specific and

macroeconomic factors on share price movements. The research was based on 26 non-financial

organisations listed on the Oman Stock Exchange, the Muscat Securities Market (MSM), over

a sample period of six years from 2011-2016. According to the author, the adoption of panel

data analysis was claimed to be more advantageous than time series analysis and cross-

sectional analysis, because it reduces collinearity or the interlinkage of the various regressors

and could arrive at more well-grounded parameters and results. The first set of hypotheses

concerning firm-specific factors was built on the semi-strong form of the Efficient Market

Hypothesis (EMH), which is an investment theory promoting the concept that all of the

information available is reflected via share prices. It means that stocks are always traded at

their fair market value, hence, it is impossible to outperform the market and attain above-

average returns without embracing more risk (Thune 2018; Kuepper 2019). Conversely, the

second set of hypotheses was founded on macroeconomic factors and the Arbitrage Pricing

Theory (APT), an alternative to the Capital Asset Pricing Model (CAPM) which presumes that

all markets are perfectly efficient (Mirzayev 2018; Hayes 2018). According to the authors,

unlike the CAPM, APT promotes the belief that stocks could be temporarily undervalued or

overvalued before the prices are eventually adjusted and rectified back to their fair market value.

Also, the APT believes that the price, risks and returns of an asset are reliant on various

macroeconomic factors.

According to Singh (2018), the research findings demonstrated a significant and positive

correlation between EPS, leverage (Debt to Capital ratio), first lag of the share price and the

dependent variable, the share prices. On the contrary, size (represented by the logarithms of

total assets), the P/E ratio and DPR’s impacts on the share prices were insignificant. The author

explained that the inconsistency of the relationship of the debt to capital ratio and share price


movements, with its theoretical relevance, might have been caused by the low percentage of

debt capital in the listed entities included in the selected sample. The IFR and GDP were also

examined as potential determinants of share prices and this is discussed in the next subsection.

Even though the research conducted analysis on both firm-specific and macroeconomic factors

which could affect the share price movements in Oman (one of the Gulf Cooperation Council

(GCC) countries), only 26 non-financial entities of the 111 entities listed were randomly

selected to be the sample and the author provided no information on the reason behind such a

sample selection. Also, both the firm-specific and macroeconomic factors were included in the

same regression model without any justification. According to Katchova (2013), independent

variables which vary by both individuals and times (firm-specific factors) and individual

invariant variables (macroeconomic factors) should not be placed in the same regression model

because of their varying nature. Also, many of the assumptions of the two theories (EMH and

APT) adopted in the study contradict with one another.

The literature review of past research which has investigated the macroeconomic factors that

affected share prices, in general, will be discussed in the next subsection.

2.3.2 Macroeconomic Factors

Macroeconomic factors are factors concerning the national economic system at an aggregate

level, for example, interest rate, inflation rate and gross domestic product (Chappelow 2017).

Adam and Tweneboah (2008), Aroni (2011, pp. 303-311), Naik and Padhi (2012, pp. 25-44),

Khan and Zaman (2012), Heng et al. (2012), Sirucek (2012, pp. 399-408), Barasa (2014),

Hussein (2017) and Singh (2018) have attempted to explore the impacts of macroeconomic

factors on share price movements.

Adam and Tweneboah (2008) founded their study on the Databank Stock Index which

represented the Ghana Stock Exchange and Aroni (2011, p. 309) founded their study on 20

companies listed on Nairobi Securities Exchange in Kenya. Both of their findings demonstrated

a positive but insignificant relationship between the inflation rate (IFR) (also referred to as the

rise of the consumer price index, CPI) and share prices. Aroni (2011, p. 310) stated that the

result was inconsistent with the theoretical concept. It was expected that a rising IFR would


have been followed by a reduction in investments and, thus, a downward share price movement.

Contrarily, Aroni (2011, p. 310) deduced that share price was adversely affected by the interest

rate (IR) and the exchange rate (ER). The claim was supported by Adam and Tweneboah (2008).

Aroni (2011, p. 310) also concluded that the money supply had a positive but small influence

over share prices while the ER had the most profound impact on them. Conceptually this was

caused by currency appreciation which would attract foreign currency inflows, enhancing

liquidity and encouraging investments (Adam & Tweneboah 2008; Aroni 2011, p. 310).

Moreover, ER stability strengthened investor confidence and attracted both local and foreign

investments.

According to Aroni (2011, p. 310), the IR also has a negative relationship with share price

movements because an increase in the IR decreases the present value of future investments and,

thus, making investment less attractive. Contrarily, when the money supply of a country falls,

its IR increases and, therefore, investors are prone to enhancing their savings and refrain from

investing. The findings were retrieved from the analysis conducted over 20 companies listed

on the Nairobi Stock Exchange and data was collected from 2008 to 2011. A short sample

period reduces the statistical power of an analysis which leads to a less reflective and reliable

result (Button et al. 2013, p. 366; Deziel 2017). Besides, Khan and Zaman (2012) supported

that the IFR was negatively related while money supply was positively related to share price

movements but the impacts of both the predictor variables were insignificant. However, this

was rebutted by Naik and Padhi (2012, p. 36) which concluded that the impacts of both the IFR

and money supply on share prices were significant. According to Naik and Padhi (2012, p. 25),

the correlation between the IFR and share prices was inverse while the money supply was

found to be positively correlated to share prices. Hussein (2017) supported that the IFR affected

share prices significantly and negatively. The entire population, all of the 16 organisations

listed on the Uganda Securities Exchange (USE), were included in the sample and data

collection was carried out over a sample period of seven years from 2010 to 2016. The research

employed a simple regression analysis to run the data and used the Efficient Market Hypothesis

(EMH) as the major theoretical reference to analyse the relationship between the IFR and share

prices. By taking into consideration only one predictor variable which might have a significant

impact on share price movements, the study is too limited to warrant what the possible

determinants of share prices are.


The findings concluded by Naik and Padhi (2012, pp. 25-44) on the correlation of the money

supply and share price movements were contradictory with the results of the analysis carried

out by Sirucek (2012, pp. 399-408) which focused on the Dow Jones Industrial Average (DJIA)

index. The DJIA represents the stock market of the United States (U.S.), as it is constituted by

the 30 largest publicly traded organisations listed on the New York Stock Exchange (Dixon

2015; Adkins 2018; Ganti 2019). Sirucek (2012, p. 399) gathered monthly data of the DJIA

value and the sample period ranged from 1959 to 2011. The research measured the money

supply using the traditional money aggregate, M2 and also money at zero maturity (MZM).

M2 comprises narrow money and its equivalents, time deposits and money market funds, while

MZM is the money supply which includes cash, checking and savings deposits, money market

securities and mutual funds (Stewart 2011). MZM is similar to M2 but more liquid which offers

almost instant access to investors for spending and consumption, because it does not include

term deposits (Hansen 2018). Granger causality tests and the Pearson Product-Moment

Correlation (PPMC) were run to arrive at the findings of the research (Sirucek 2012, p. 399).

The results indicated that the effect of MZM on the DJIA value was more significant than M2,

but money aggregates had an inverse correlation with share prices. The research only

investigated one macroeconomic factor, without any consideration on other factors.

Furthermore, by analysing only the 30 most prominent blue-chip organisations in the U.S., the

findings were not a representation of many other sectors in the country (Adkins 2018).

Heng et al. (2012) agreed that the IR and IFR were inversely related to share prices while the

money supply had a positive relationship with share price movements and the effects were

significant. Based on the analysis, the crude oil price, unexpectedly, had no consequential

impact on share prices. The authors stated that the result could be caused by the inclusion of

the effects of the two GFCs that occurred during their sample period. The KLCI (composite

market index in Malaysia) was utilised as the proxy for stock market returns, indicating that

only the impacts on the top 30 companies listed on Bursa Malaysia were analysed. Refutably,

Barasa (2014) concluded that the positive or negative relationships between share price

movements and macroeconomic variables, namely; the IFR, GDP and money supply were all

insignificant. The author claimed that the unstable political environment in Kenya over their

sample period was the rationale behind the insignificance of those factors because investors

were majorly deterred by the political upheavals. None of these studies took into consideration

the impacts of firm-specific factors, such as MC, EPS, NAV, the P/E ratio and DPS.


Dissimilarly to most past studies, Singh (2018) researched 26 non-financial organisations listed

on the Oman Stock Exchange and included both firm-specific and macroeconomic predictor

variables in the analysis. The author agreed with Heng et al. (2012) and Barasa (2014) that the

IFR had a significantly negative correlation with share prices, whereas, the impact of the GDP

on share price movements was insignificant. The limitations of the study were the selective

inclusion of only 26 non-financial organisations from the 111 organisations listed on the

Muscat Market Securities and the opposing assumptions of the theories (EMH and APT)

applied in the research. Also, the practicality of the adoption of both the EMH and APT, in

reality, is largely disputed. According to Kuepper (2019), the EMH claims that share prices

will never diverge from their fair market values and that the market could never be beaten but

in practice, many investors like Warren Buffett have consistently beaten the market, taking the

opportunity of the deviations of share prices from their fair values. Moreover, it is very

challenging and impractical to apply the APT in reality because of the complicated statistical

analysis and heavy data needed (Mirzayev 2018; Hayes 2018).

2.4 Factors that Drive the Movements of REIT Share Prices

In the past two decades, researchers, such as Ziering, Liang and McIntosh (1999, pp. 61-67),

Conover, Friday and Howton (2000, pp. 41-63), Below, Stansell and Coffin (2000, pp. 263-

278), Clayton and MacKinnon (2000), Strange and Tang (2000), Brent et al. (2011, pp. 31-42),

Ying (2004), Cheong et al. (2006), Ali (2006), Ong, Teh and Chong (2011, pp. 1-15), Hooi and

Smyth (2011), Ito (2013), Mohammad and Zolkifli (2013), Chiang (2014), Olanrele (2014, pp.

492-502), Wong (2015), Fang et al. (2017, pp. 242-253) and Diedrich (2017) have investigated

the relationships between several factors namely; the interest rate (IR), inflation rate (IFR),

debt to asset ratio (D/A ratio), debt to equity ratio (D/E ratio), price-earnings ratio (P/E ratio),

earnings per share (EPS), dividend yield (DY), dividend per share (DPS), net income (NI), net

asset value (NAV) and market capitalisation (MC) and the share price movements of REITs.

Table 3 shows information regarding past research conducted on the factors affecting the

movement of REIT share prices.


Table 3: Previous Studies on the Factors that Drive the Movements of REIT Share Prices

No Researchers Independent Variables Analysed

Year Market Firm-Specific Macroeconomic

1 Ziering, Liang

and McIntosh Market Capitalisation (+) 1999 USA

2 Conover, Friday

and Howton Market Capitalisation (+) 2000 USA

3 Below, Stansell

and Coffin Market Capitalisation (+) 2000 USA

4 Clayton and

MacKinnon

NAV (+),

Market Capitalisation (+) 2000 USA

5 Strange and

Tang

Debt to Equity

(D/E Ratio) (-),

D/A Ratio (-),

DY (+),

Market Capitalisation (-)

2000 USA

6 Ying NAV (+) 2004 Asia-

Pacific

7 Ali Market Capitalisation (+) 2006 Malaysia

8 Brent et al. NAV (+) 2011 USA

9 Ong, Teh and

Chong NAV (+) 2011 Malaysia


10 Mohammad and

Zolkifli

NAV (+),

DY (+),

Net Income (NI)

(Insignificant),


2013 Asia

11 Chiang DY (+) 2014 USA

12 Olanrele

NAV (+),

NI (Insignificant),


2014 Malaysia

13 Cheong et al. IR (-) 2006 USA and

UK

14 Hooi and Smyth IR (-) 2011 Malaysia

15 Ito IR (-) 2013 Japan

16 Wong IR

(Insignificant) 2015 Malaysia

17 Fang et al. IR (-),

IFR (-) 2016

Japan,

Singapore

and China

18 Diedrich IR

(Insignificant) 2017 USA


2.4.1 Interest Rate and Inflation Rate

REIT share prices were influenced by the fluctuations of the interest rate (IR) and the impacts

were significant and long-term while the correlation was negative (Cheong et al. 2006). The

analysis was carried out on the REITs and market indexes in the United States (U.S.) and the

United Kingdom (UK) and the sample period ranged from 1900 to 2005. Nevertheless, the

study did not focus on the factors affecting share price movements, in general, or of REITs, but

rather on how securitised real estate sectors, including the REIT industry, were impacted by

equity and fixed income markets. Also, the study investigated the contrast between permanent

and transitory factors.

According to Ito (2013), the share prices of Japanese REITs (J-REITs) would experience a

downward movement when the country’s IR rose. The author analysed two samples: sample

one was run from March 2003 to January 2007, while sample two was run from June 2007 to

January 2013. All of the REITs listed on the Tokyo Stock Exchange (TSE) were included in

the analysis and Ordinary Least Square (OLS) method was adopted to estimate the correlations

between the IRs and the share prices. The findings demonstrated that the negative impacts of a

rising IR on the share prices of REITs in Japan were greater in sample two. Ito (2013) reasoned

that this was due to the strain of procuring funds, with the occurrence of the global financial

crisis (GFC) in 2007-2008. Furthermore, the research explored mainly on the IRs and the stock

market as the drivers of the J-REIT market and found that different types of IRs had varying

significance on the market. The findings of sample two also deduced a more significant

negative correlation between the swap rates and the share prices of J-REITs, as compared to

Japanese Government Bond (JGB) yields. The rationale behind such a trend was swap rates

being the benchmark IRs set by the Japanese government for mid to long-term loans.

The impacts of IR and the IFR on the REIT indexes in Japan, Singapore and China were also

studied by Fang et al. (2016, pp. 244-245) because the REITs in Japan and Singapore owned

the most substantial market capitalisation among the REIT markets in Asia, whereas, Chinese

REITs have been signalled as the most rapidly expanding REIT market in Asia. The research

adopted the Autoregressive Distributed Lag Model (ARDL) to examine if there were any

correlations between IR and the IFR respectively with REIT share prices, and the Granger Non-

Causality Test to discover if there were a significant unidirectional relationship between the


two regressors and REIT share prices in those countries. The ARDL test concluded that the

impacts of IR and the IFR on the REITs in Singapore and China were significant, negative and

long-term. On the contrary, the impacts of IR on the Chinese REITs showed a low degree of

significance, which the results of the Granger Non-Causality Test agreed with. The authors

stated that a rising IR environment might only impact Asian REITs with higher capitalisation.

The authors concluded that through the different methods used to analyse the data, a significant

and negative correlation was found between IR and the share price movements of REITs. The

IFR was also found to be significantly and negatively correlated to REIT share prices.

According to Fang et al. (2016, p. 245), as the establishment dates of the REIT indexes in the

three countries varied, all of the indexes were considered to inaugurate on the same date as the

Chinese REIT index. Therefore, the sample period was restricted to include merely the data

from March 2008 to July 2012. The restraint might have affected the reliability of the results,

especially, the analysis of the Japan and Singapore REIT indexes.

Besides, Hooi and Smyth (2011) and Wong (2015) studied the impacts of IR fluctuations on

the REITs in Malaysia. Hooi and Smyth (2011) supported that IRs and REIT share prices were

deemed to be negatively and significantly correlated. The authors attempted to study the

relationship between REITs, interest rates and share prices in Malaysia. The analysis was

carried out on 13 M-REITs by applying the Augmented Dickey-Fuller (ADF) unit root tests,

followed by the Lagrange multiplier (LM) unit root test. The authors deduced that the LM unit

root test was the preferable methodology because it reduced the impact of a structural break on

its statistical properties. The findings demonstrated a negative and significant relationship

between changes in the IRs and most of the REIT share prices. However, they only collected

data from 2006-2009 comprising 13 REITs. Button et al. (2013, p. 366) and Deziel (2017)

stated that a short sample period of a few years reduces the statistical power of a study, making

it less reliable in reflecting a true result. Hooi and Smyth (2011) also claimed that the M-REIT

industry remained underdeveloped, thus, making it a bad proxy for investment in real estate.

The authors reasoned that the participation of Malaysian investors in REIT markets was

relatively small, as compared to many other countries, due to the lack of awareness.

Nonetheless, the claim was rebutted by Osmadi (2010), Wong (2014) and Ernst & Young

Global Limited (2016). They asserted that Malaysia, as one of the emerging REIT markets,

renders great investment opportunities.


On the contrary, according to Wong (2015), the integration between the IR and M-REIT returns

was weak, even though the findings showed a stronger negative correlation between the two

variables in the long-term proxy rather than in the short-term proxy. This was agreed by

Diedrich (2017) who analysed the correlation between IR fluctuations and a renowned REIT

index in the United States, namely; the MSCI US REIT Index. In the isolated case study, a

linear regression model was adopted over a 10-year dataset and the results demonstrated an

insignificant correlation between the IR and REIT share prices. The analysis also showed that

the impacts could swing from being insignificant to significant and from positive to negative

correlations, which relied on the causes of IR fluctuations.

Also, Wong (2015) found that IRs had a more significant impact on M-REIT returns during

the pre-GFC subperiod. The study calculated the nominal rate of return by balancing off the

difference of the dollar amount invested and the dollar amount of the returns without adjusting

for expenses, akin to taxes and inflation. The analysis was built on 17 M-REITs (the entire

population of REITs listed on Bursa Malaysia) over a sample period of approximately eight

years from August 2005 to December 2013. Furthermore, the Pearson Product-Moment

Correlation (PPMC) and a multifactor model were adopted to test the hypotheses of the

research. The author reasoned that the lack of significance in the correlation of the two variables

might be caused by the higher conformity of the REIT structure with stocks rather than with

bonds and, thus, REITs are not purely yield driven like bonds, which are highly sensitive to IR

fluctuations. However, conceptually this would be highly disputable as REITs are known for

their characteristics that are modelled after mutual funds (Learn about REIT basics 2018). The

study concentrated not only on the impacts of the IR on M-REIT returns but more on the

characteristics of M-REITs as a whole. The author stated that there were signs of significant

differences between the sensitivity of conventional and Shariah-compliant REITs to yields and

therefore, the IR, but this was not investigated further in the study. Also, the lack of integration

between the returns of M-REITs and those of the regional REIT market was claimed to be an

obstacle for the development of M-REITs because it made M-REITs less appealing among

potential investors internationally.

Conceptually, a higher IR will normally have a negative influence on REIT share prices,

because a rising IR implies that there will be a reduction in the present value of the REIT’s


future cash flows, including bond coupons and stock dividends (Zambell 2018). However, Lake

(2018) affirmed that although REITs are typically perceived as IR sensitive, it depends on why

the IR is rising or falling. Thus, the IR may not necessarily have a significant impact on or an

inverse relationship with REIT share prices. This was supported by Osterland (2018) who

claimed that in a rising IR environment, it might be advisable to purchase REITs, instead of

selling them, if the IR were rising, because the economic climate was strengthening.

2.4.2 Earnings, Dividends and Net Income

A REIT’s stock value is dependent on earnings, and the expectations around earnings tend to

steer the movements of REIT share prices also (Block 2011, p. 14). The common indicators of

a REIT’s earnings are Net Asset Value (NAV), Net Income (NI), Asset Value, Dividend Yield

(DY) and Dividend per Share (DPS). According to Strange and Tang (2000), DY had a

significant positive influence on the movements of REIT share prices as it represented a firm’s

commitment to distribute profits to its shareholders. This was supported by Chiang (2014) who

studied the relationship of DY and REITs’ share price movements through five REIT portfolios

retrieved from the CRSP/Ziman Real Estate Database. According to Mordkoff (2016), the

distribution is likely to be skewed when a small sample size is being analysed. The data

collection ranged over approximately 22 years, and two sample periods were used to conduct

the analysis: sub-period one, was from 1980 to 1992 while sub-period two, was from 1993 to

2011. According to Chiang (2014), sub-period one represented the vintage REIT era before the

structural change in REIT pricing had taken place, whereas, sub-period two represented the

modern REIT era. OLS regression was used and the findings concluded that DY reflected new

information in the vintage REIT era and, thus, the aggregate dividend growth of REITs could

be predicted from their aggregate DY. However, a significantly positive correlation between

DY and REIT prices only appeared in sub-period two, after the structural change in REIT

pricing.

Moreover, in a study conducted by Olanrele (2014, p. 500), NAV and NI were found to be

positively related to the dividend payout, which was regarded as the representation of a REIT’s

returns, driving REIT share prices in Malaysia, but the impacts of NI on them were insignificant.

Multiple regression analysis was adopted, and data were collected from 2007 to 2013. The

author reasoned that favourable earnings historically, or for the current period, would lead to


favourable earnings estimates and that REIT share prices were established on the potential and

existing investors’ expectations of the REIT’s future earnings capabilities. However, the result

of Olanrele (2014, p. 492) focused on merely a single REIT listed on Bursa Malaysia. Hence,

according to the author, it did not represent the aggregate result of M-REIT share market

reactions. Only one M-REIT was analysed because the study was conducted as pilot research

and extended research needed to be carried out in the future (Olanrele 2014, p. 500). These past

studies excluded macroeconomic factors which could potentially impact share prices crucially.

2.4.3 Financial Leverage and Gearing

Financial leverage, which is also referred to as trading on equity, is the utilisation of debt to

acquire additional assets, while gearing is defined as the relationship between a firm’s debt and

its equity capital (Averkamp 2018). They are both perceived as imperative indicators of a firm’s

performance, as well as its management efficiency and effectiveness. According to Strange and

Tang (2000), a higher level of debts represented through the debt to equity (D/E) and debt to

asset (D/A) ratios had inversely affected REITs’ share price movements. According to

McClellan (2018), these ratios are more conservative leverage measures. The results were

inconsistent with the findings of Olanrele (2014, p. 500), which stated that gearing and leverage

had an insignificant and positive relationship with REIT share prices. Nevertheless, the

financial performance ratios used to represent leverage and gearing were not mentioned and,

therefore, the result was not taken into account for this research. Furthermore, as discussed

above, Olanrele’s (2014, p. 492) findings could not represent the aggregate result of M-REITs’

share price movements because only one REIT listed on Bursa Malaysia was analysed.

Although Strange and Tang (2000) conducted their study by collecting the data of 143 REITs

listed on Standard and Poor’s (S & P) 500 index across the years 1990-1999, it ignored the

impacts of macroeconomic factors on the REIT share prices.

According to McClellan (2018) and McKeough (2019), conceptually, the most typically

applied and suitable ratio to study a REIT’s leverage or gearing is debt to market capitalisation

or the debt to capital ratio, which is the common stock equity added up with preferred stock

equity and total debt. McClellan (2018) expressed that NAREIT also referred to the

denominator of the debt ratio as the sum of market capitalisation and total debt. The debt to

market capitalisation ratio provides a better insight into a REIT’s financial variability as it


measures a REIT’s debts against its capital raising competence (Collins 2017). Also, the actual

worth of an organisation’s assets (both physical and intellectual) is reflected in its market

capitalisation. This is not the case when only the book value or fair value of the total assets is

included in the leverage estimation (McKeough 2019). Other debt ratios could be the D/A ratio,

D/E ratio and the debt-to-EBITDA ratio. McClellan (2018) stated that the D/A ratio, as

compared to the debt to market capitalisation ratio, is a more conservative leverage measure as

a denominator, the total asset value is derived from the book value of the total assets of a REIT

instead of using the market value. The book value is not a precise portrayal of the assets, as it

ignores the fact that some assets have depreciated. Although theoretically debts, REIT returns

and share prices are inversely correlated, a desirable level of leverage and gearing relies on the

risk appetite of investors in the respective REIT sector (McClellan 2018).

2.4.4 Net Asset Value

A REIT’s valuation is also closely related to the net market value of its assets, net of its

liabilities and obligations (Block 2011, p. 223). This is known as the net asset value (NAV),

where the assets comprise the REIT’s property. According to Block (2011, p. 223), NAV per

share divided by the number of outstanding common shares is often perceived as one of the

major factors that determine the share prices of REITs. Thus, to favourably enhance a REIT’s

share valuation, the company’s property portfolio should be intensified via consistent capital

expenditure. The author also claimed that the maintenance and growth of NAVs are anticipated

through such strategic portfolio enhancements which furnish as well as form the foundation of

a REIT’s share price appreciation.

Clayton and MacKinnon (2000) studied the impacts of NAV fluctuations of REITs on their

leverage, market capitalisation and liquidity, and this had, in turn, driven REIT share prices.

The data collection was carried out from the year 1996 to 1999, a relatively short period

because it focused mainly on the contrast of REIT market reactions during the pre-downmarket

period (the years 1993 to 1997) and the post downmarket period of 1998 to 1999. The findings

showed that the magnitude of the premium to NAV had a positive relationship with the market

capitalisation of REITs and the study assumed higher market capitalisation would lead to a

rising share price. Furthermore, the deviations of REIT share prices from NAV evinced

consistency with the noise theory, in which it was believed that such deviations were caused


by irrational investor sentiment. According to the authors, when irrational investors had a

pessimistic outlook on the REIT markets, it created additional risks for investors who behaved

rationally, as it was challenging to predict how the behaviours of irrational investors would

influence share prices. It was also claimed that investors’ perception of REITs as growth stocks

in the pre-downmarket period attracted noise traders, impelling the prices to rise. During the

downmarket and post-downmarket periods, REITs were no longer regarded as growth stocks

and, thus, the noise traders were deterred from investing. Therefore, REIT share prices no

longer deviated substantially from NAV, leading to a clearer and more significant positive

correlation between NAV and REIT share prices (Clayton & MacKinnon 2000). However,

extensive research needs to be conducted to verify such assumptions in the modern REIT era,

as the research was conducted in the nineties.

According to Brent et al. (2011, p. 41), the growth of REITs was dictated based on the NAV

per share, instead of the book value per share, as the trading decision was stimulated by NAV.

REIT share prices and NAV were closely correlated both in the short-term and the long-term,

be it the individual property market or the REIT market as a whole (Ying 2004). Furthermore,

the studies also indicated that NAV based property stock valuation theory could be relied upon

as the primary foundation for REIT performance assessment. They consistently agreed that

NAV was a major factor driving the prices of REIT shares and that the correlation was deemed

positive.

Furthermore, Mohammad and Zolkifli (2013) carried out an analysis on 45 REITs which were

listed on the stock exchanges of Taiwan, Thailand, Malaysia, Hong Kong, Japan and Singapore.

The findings revealed that the factors to be taken into consideration by investors in determining

REIT returns and NAV, were DY, NI and size or market capitalisation. The performance was

measured using a proxy of return and NAV. The findings exhibited that not only did NAV have

a positive relationship with share prices, but it was also significantly and positively correlated

with DY and market capitalisation. Furthermore, the authors used beta to represent systematic

risk, which is risk inherent to the entire REIT market. The result showed that when beta or

systematic risk was greater, both returns and NAV of the REITs were lower, and vice-versa

but the significance was relatively low. This evidenced the benefit of REITs as a less risky

alternative investment with potential for earnings enhancement, as opposed to regularly listed


equity stocks. The result of NI indicated a negative and significant correlation with NAV but

not significant with share price returns. On the contrary, the results for size both showed

positive and significant correlation with return and NAV. Mohammad and Zolkifli (2013)

carried out their research by adopting multiple regression analysis. The sample period ranged

from 2007-2011 and a sample of 45 listed REITs was randomly selected from Thailand, Taiwan,

Malaysia, Japan, Singapore and Hong Kong. The authors stated that their findings did not

represent the aggregate results of the whole Asian REITs industry, nor for any of the individual

countries analysed. They also claimed that extended research should be carried out to include

additional possible factors that cause REIT share prices to fluctuate.

Besides, Ong, Teh and Chong (2011, p. 1) examined the performance of M-REITs from the

year 2005-2010 based on the Net Asset Value (NAV) approach. 13 M-REITs were examined

and data collection for those listed after 2005 only began from the dates of their establishment.

The findings stated that NAV had a positive and significant correlation with share prices. The

study also categorised NAV into NAV premium and NAV discount and the findings

demonstrated that REITs which traded in NAV premiums had superior historical and future

earning capabilities, organisational and operational efficiency and quality of management. On

the contrary, NAV discounts occurred when it traded below the current share prices which

reflected poor current and future prospects for earnings and mistakes in financing and

operations decisions. However, the author claimed that M-REITs were good investment

options because they were mostly traded on NAV premiums, but the reasoning behind such a

statement was not sufficiently supported. The research methodology was also indistinct, only

the NAV approach and some theories adopted to form the foundation of the research were

stated. Moreover, the study concentrated more on the reactions of individual REIT stocks

towards their NAV position, instead of an aggregate insight into the REIT market in Malaysia

or REITs in general.

2.4.5 Market Capitalisation

Market capitalisation is the total dollar value of a company’s outstanding shares and in the

REIT industry, it represents the size of the REIT (Seth 2018). Strange and Tang (2000) stated

that small-scale REITs had more favourable performance than larger entities. The findings of

Strange and Tang (2000) demonstrated that REIT size was negatively related to returns, where


small-scale REITs provided greater returns, without higher risk involvement. According to the

authors, small-capitalisation REITs were more susceptible to a rise in share prices because they

provided better potential for growth in the long-run. This was agreed by Mueller (1998, pp.

149-157) who asserted that a larger REIT size might be an indication of more challenges

instead of higher earnings, returns and share prices.

Nevertheless, the findings of Conover, Friday and Howton (2000, p. 162) indicated that larger

entities provided a higher return but lower risk than small-scale corporations. The relationship

between the two was proven to be an issue of controversy. The size of real estate holdings was

a dominant moderator of risk and return across the spectrum of size, where investors in the

largest REITs yielded the highest return on investment, but sustained the greatest volatility as

well (Ziering, Liang & McIntosh 1999, p. 65). Below, Stansell and Coffin (2000, p. 277) also

supported that market capitalisation was the most significant component affecting the returns

of REITs owned by financial institutions, because the bigger the size of a REIT, the better

access it had to capital markets, economies of scale and liquidity. Negative cost elasticity

related to REIT interest expenses indicated that larger REITs had superior access to

institutional capital. These studies focused mainly on the relationship between market

capitalisation and the share price movements of REITs, without taking into consideration the

influences of other factors, both firm-specific and macroeconomic, on REIT share prices.

The outcomes of the research carried out on the linkage between the market capitalisation and

share prices of REITs in the different markets varied. The paper published by Ali (2006)

investigated the relationship between the size and performance of real estate stocks based on

30 real estate shares on Bursa Malaysia selected by random choice out of the total of 88 real

estate related stocks. The sample comprised; large, medium and small-scale real estate stocks

and the sample period ranged from the year 1992 to 2003. The Sharpe ratio and a coefficient

of variation were adopted and the study concluded that a higher return and lower risk were

derived from large capitalisation real estate stocks. A lower risk was more easily attained

through the distribution of risks with a diversified portfolio than other forms of real estate

stocks. The research included not only the M-REITs but also other stocks that were real estate

related. The author suggested that more precise research could be conducted on the M-REIT

industry alone or real estate stocks listed on Bursa Malaysia. Also, Olanrele (2014, p. 500)


indicated that REITs’ market capitalisation and their share prices were positively related.

Nonetheless, the findings were based on only one REIT in Malaysia, therefore it did not

represent the aggregate result of M-REITs’ share price movements.

2.5 Shariah-Compliance as a Firm-Specific Factor

Other than the factors which drive the movements of share prices, in general, and those of the

REITs, specifically, past studies had investigated the impacts of Shariah-compliance on share

price movements, in general, and in the REIT industry.

Shariah-compliant REITs are perceived to have good prospects, but not without trials. The

challenges to its international establishment include the inadequately defined REIT rules and

standards that govern the listing and running of Shariah-compliant REITs in most countries.

Furthermore, according to Islamic Markets (2018), the variations in terms of the Sharia

interpretations of the jurisdictions in various countries impose more challenges to the growth

of Shariah-compliant REITs. The Malaysia International Islamic Financial Center (MIFC)

(2013) asserted that the development of Shariah-compliant REITs in some regions, for instance,

the Gulf Cooperation Council (the GCC is the intergovernmental union comprising seven Arab

states of the Gulf monarchies) was impeded by the 2008 global financial crisis (GFC). Hence,

the inauguration of many Shariah-compliant REITs was shelved due to the GFC. Adair et al.

(2009) emphasised that the adverse impacts of the GFC were great, especially, on industries

related to real estate and tangible assets.

According to Miniaoui, Sayani and Chaibi (2015, p. 357), there was a widely proliferated

conception that Shariah-compliance lowered the risk borne by an entity and therefore, its

investors. It was also believed that they were more resilient against shocks, for example, the

GFC, which had grappled the economies of many countries. However, Miniaoui, Sayani and

Chaibi (2015, p. 367)’s findings showed that the risk profile of Islamic index in GCC was

similar to the conventional indexes. While the adverse impacts of GFC were apparent in the

world’s economies, Shariah-compliant REITs in Malaysia had proven to be more defensive

against shocks than the conventional M-REITs, as well as the other conventional and Islamic

REIT markets internationally (Newell & Osmadi 2009, p. 329).


The advantages of issuing or investing in Shariah-compliant REITs, as compared to

conventional REITs, include more favourable returns and tax incentives and lower credit risk

(Shamasundari 2016). Ahmad Tajjudin Rozman et al. (2015, pp. 8-9) asserted that the Shariah-

compliant REITs in Malaysia had outperformed not only the conventional REITs but also other

asset classes, such as bonds and shares, in terms of their average returns. Despite the results

demonstrating a higher risk borne by Shariah-compliant REITs, as compared to bonds, the

authors affirmed that they were still perceived as a better investment option by having a lower

risk-return ratio. According to Ahmad Tajjudin Rozman et al. (2015, pp. 8-9) and Nordin

(2018), Shariah-compliant REITs also offer more flexibility and diversification for investors

than other asset classes which increase the efficiency of portfolio management. Ting and Noor

(2007) and Ahmad Tajjudin Rozman et al. (2015, pp. 8-9) agreed that Shariah-compliant M-

REITs play a vital role in strengthening the competitiveness of the country’s Islamic financial

instruments by attracting Muslim investors to channel their focus and investment into Shariah-

compliant assets and funds.

Mohamad (2015) studied the differences between the performance of conventional REITs and

the Shariah-compliant REITs listed on Bursa Malaysia. The analysis compared the dividend

yield (DY), net asset value (NAV) and earnings per share (EPS) of the two varied REIT

structures. 13 M-REITs were analysed and the secondary data on those REITs were collected

through Bloomberg’s database, with a sample period of five years, from 2009 to 2013. Button

et al. (2013, p. 366) and Deziel (2017) claimed that theoretically, a short sample period of a

few years lessens the statistical power of research and, therefore, reduces its probability to

reflect a reliable result. Furthermore, one-way ANOVA analysis was adopted in the research

where the main function was to estimate if the means of two or more datasets were dissimilar

statistically. The author stated that the rationale for adopting ANOVA to carry out the analysis

was the unequal sample size of the two REIT structures. According to Davies (2018), ANOVA

very often produces a misleading outcome unless it is used in a controlled study where the

samples are perfectly independent. Davies (2018) also stated that the result produced by

ANOVA could only confirm if one group in the analysis varied from at least one other group,

but does not give any information on the number of groups that are dissimilar statistically and

could not identify the dissimilar groups. Therefore, according to Davies (2018), ANOVA is

not a suitable statistical analysis software under many circumstances. Mohamad (2015)’s

results demonstrated that Shariah-compliant REITs in Malaysia had significantly superior


performance than the conventional REITs in terms of their NAV and EPS while the difference

between the DY of the two REIT structures was insignificant. Nevertheless, the author did not

provide any possible reasoning for such an outcome.

Besides, Foo and Muhammad (2015) assessed the behaviours of Shariah-compliant REITs and

compared them to those of conventional REITs. By adopting the time-varying capital asset

pricing model (CAPM), they evaluated the stochastic abnormal returns (alphas, a measure of

performance on a risk-adjusted foundation) and systematic or market risks (betas, also referred

to as volatility). They collected data through Bursa Malaysia on 15 M-REITs for a period of

10 years, from 2005 to 2014. Two of the M-REITs adhered to the Sharia law. The sample

period was subdivided into three subperiods to dovetail with the three noteworthy events in the

Shariah-compliant M-REITs industry. The three events included; the debut of the first Islamic

REIT on Bursa Malaysia, the privatisation of Al-Hadharah Boustead (the first and sole Shariah-

compliant plantation REIT in Malaysia) and the relisting of the Axis REIT as an Islamic REIT.

According to Foo and Muhammad (2015), Shariah-compliant REITs had superior performance

with regard to abnormal returns and lower systematic risks. The authors also claimed that

Shariah-compliant REITs fit as a counter-cyclical investment, an investment decision made

acting against the market trend. Furthermore, based on the findings, Shariah-compliant REITs

were likely to offer arbitrage opportunities for investors.

Yazi, Morni and Song (2015, p. 1019) also investigated the impacts of Shariah-compliance as

a potential factor driving the share price movements on Bursa Malaysia. However, the research

did not focus on the M-REIT sector, but rather on all of the Shariah-compliant entities listed

on Bursa Malaysia. The conversion of 18 non-Shariah compliant stocks into Shariah-compliant

stocks and the disqualification of 158 stocks from being listed and categorised as Shariah-

compliant stocks at the end of 2013 founded the basis of the research. The dramatic shifts were

attributable to the revised screening framework and new benchmarks adopted by the Securities

Commission Malaysia (SC) for Shariah-compliance evaluation. According to the authors, the

conversion of 18 non-Shariah compliant stocks was caused by the lower benchmarks set

regarding the level of mixed contributions of typically allowable activities and the financial

ratios bearing interest (riba) elements. The sample period ranged from six months before

December 2013 to 60 days after it and the data of the entities were gathered through Datastream


International. Cumulative abnormal returns (CARs) was adopted to evaluate the impacts of

Shariah-compliance on share prices. The result showed a significant and positive correlation

between the Shariah-compliance of an entity and share price movements.

Similarly, Mohamed and Lusyana (2017, p. 7) collected data on 33 randomly selected securities

that were listed as Shariah-compliant companies on the Indonesian stock exchange during the

sample period from 2010 to 2014. The research was founded on an event study methodology

and CARs was also adopted, where the estimation window ranged from 30 days before the

event and 60 days after it. Mohamed and Lusyana (2017, p. 21) concluded that Shariah-

compliance had significantly affected the share prices to rise. The authors justified that

investors were becoming more inclined towards ethical decision making rather than merely

profit-making. This was supported by Rosly (2018) who asserted that delisting a public entity

from being Shariah-compliant would cause the share price to fall significantly. Nevertheless,

Rosly (2018) also stated that past studies focusing on this area had shown mixed results on the

effects of delisting Shariah-compliant securities on share price movements and Islamic

investments. Therefore, the signals conveyed to existing and potential investors were

conflicting regarding the appropriate investment decisions to make on Shariah-compliant

securities or Shariah-compliance announcements.

Farooq and Alahkam (2016) agreed that Shariah-compliant companies offered lower volatility

but rebutted the claims of most past studies by stating that Shariah-compliant stocks had weaker

performance than conventional companies. The research was carried out on non-financial

conventional and non-financial Shariah-compliant companies listed on the stock exchanges of

the MENA region. The countries included in the MENA region were Morocco, Egypt, Saudi

Arabia, the United Arab Emirates, Jordan, Kuwait and Bahrain. The data collection was carried

out from 2005-2009 and pooled OLS regression analysis was adopted. A dummy variable was

created to indicate if a company was Shariah-compliant or conventional. Farooq and Alahkam

(2016) argued that the Shariah-compliant companies in the MENA region underperformed

because their financial characteristics were less favourable under normal economic conditions,

as compared to the conventional companies. For example, conventional companies could have

higher retained profits which they could utilise to fund large capital expenditures, while

Shariah-compliant companies were required to distribute most of the profits to their


shareholders. Nonetheless, the analysis only studied the Shariah-compliance of the securities

as a potential driver of share price movements without taking into consideration other firm-

specific and macroeconomic factors. The authors expressed that the outcomes on different

industries and countries could vary, and therefore, further research needed to be conducted.

Reddy and Fu (2014) also deduced that Shariah-compliant companies were less stable and less

shielded against market volatility. Thus, the risks investors had to bear with Shariah-compliant

companies were greater than those who invested in conventional companies. The sample

included 50 Shariah-compliant and 50 conventional companies listed on the Australian Stock

Exchange which had the largest market capitalisation. They collected weekly data on the 100

companies for the period from 2001-2013 and the analysis was conducted by adopting the

Mann Whitney U Test, sometimes referred to as the Wilcoxon Rank Sum Test. According to

the authors, the rationale behind such contrast from the findings of most of the past studies was

the lack of diversified portfolios in the Australian Islamic market.

Dissimilarly from the abovementioned past studies, Morad and Masih (2015) compared the

reactions of Shariah-compliant REITs and conventional REITs against macroeconomic

indicators, inflation and interest rate fluctuations. The sample comprised of all of the REITs

listed on the Singapore stock exchange and Bursa Malaysia, but only five of the smallest and

largest REITs from the London stock exchange. There were 62 REITs observed, however,

among the 10 REITs listed on the London stock exchange, there were no Shariah-compliant

REITs. The data were collected from 2007 to 2015 through Thomson Reuters Eikon.

Furthermore, a Markov switching model was applied in the analysis because there were varied

regimes in the three different stock exchanges. According to Kuan (2002), Hamilton (2005)

and Brandel (2017), the model comprises of multiple equations which denote the time series

behaviours of the varied regimes and assumes that fixed transition probabilities could be

imposed to oversee the fluctuations between the various state variables. Morad and Masih

(2015) found that the impacts of IFR and IR fluctuations on the Shariah-compliant and

conventional REITs were not significantly dissimilar, but the rationale behind this was unclear.

A considerable number of past studies have investigated the impacts of Shariah-compliance on

REITs’ performance and share price movements but without considering other firm-specific

and macroeconomic factors.


2.6 Summary

This chapter has discussed both the factors which drive share prices, in general, and the REIT

share prices identified in past research. Furthermore, not only past studies that focused on the

firm-specific factors and macroeconomic factors were looked into, but those examining the

impacts of Shariah-compliance on REIT share price movements were also included. The

literature review helped to establish the framework and the focal point of this research, while

the next chapter on research methodology details the systematic plan that was carried out to

conduct the research.


CHAPTER THREE METHODOLOGY

3.1 Introduction

This chapter details the approach that was taken to investigate the research problem, the

methods adopted to collect and analyse data and the rationale behind the use of specific

procedures to identify, select and analyse the information collected.

There were two phases to this study. In the first phase, the factors that could drive share price

movements were identified through a literature review. In the second phase, a variable selection

process was conducted to investigate the relationship between each of the selected independent

variables and REIT share prices.

To evaluate the relationships between the potential factors and the dependent variable, past

studies which have analysed the factors that drive share price movements have adopted various

research methodologies. For instance, a linear regression model was adopted by Diedrich

(2017); a multiple regression model was adopted by Olanrele (2014, pp. 492-502), Heng et al.

(2012) and Mohammad and Zolkifli (2013); an ordinary least squares regression model (OLS)

was adopted by Ito (2013) and Chiang (2014); the capital asset pricing model (CAPM) was

adopted by Below, Stansell and Coffin (2000, pp. 263-278) and Ali (2006); balanced panel

data analysis (Pearson’s correlation) was adopted by Kodithuwakku (2016, pp. 67-76);

unbalanced panel data analysis (Pooled least squares model) was adopted by Strange and Tang

(2000); panel data analysis, by both fixed and random models were adopted by Aveh and Vitor

(2017) and Singh (2018) and the vector error correction model (VECM) was adopted by Adam

and Tweneboah (2008) and Hooi and Smyth (2011).

This chapter illustrates the research methodology and design that were adopted by the research.


3.2 Research Philosophy

According to Chetty (2016), a research philosophy is a belief regarding the method in which

data about a phenomenon should be collected, analysed and adopted. A positivist research

paradigm is a philosophy that adheres to the perspective that only factual knowledge obtained

through observations (which include measurements) is reliable, where the researcher is

restricted to data collection and interpretation through objective reasoning (Research

Methodology 2017). The research findings are usually observable and quantifiable. Due to the

nature and topic area of this research, which is to quantify the relationship between each of the

independent variables selected and M-REIT share prices, a post-positivist research paradigm

which is highly associated with quantitative methodology as a means of gathering data was

more suitable and, thus, adopted. Post-positivists acknowledge that all of the observations

could be erroneous and all of the theories can be revised.

Furthermore, the research is also an empirical study, with a close analysis of secondary data

and deductive research. According to Sheffield Hallam University (2017), deductive research

is theory-testing, which involves drafting hypotheses based on existing theory, or theories, and

developing a research strategy to test the hypotheses. It is often linked to datasets, surveys or

quantitative analysis. The following subsections discuss the research methodology in detail.

3.3 Research Framework

According to Sousa, Driessnack and Mendes (2007, p. 503), a research design is a framework

adopted for the research planning, implementation and analysis to address the research

questions, or to verify the hypotheses. The following paragraphs explain these components

with more details.

3.3.1 Identification of Factors through Literature Review and Synthesis

Other than their theoretical relevance, the rationale behind the independent variables selected

to be analysed in past studies which focused on factors driving share price movements, in

general, or in the REIT market is vague. Although the review of literature itself does not suffice

as a research method, for this study, the literature was not only reviewed but critically analysed

and synthesised, where the findings and elements of various past studies were combined to


form a new whole, comparing and concluding the findings gathered (Kowalczyk & Truluck

2013, pp. 219-220). Therefore, both potential firm-specific and macroeconomic factors that

would drive the share price movements of REITs were identified through the literature review

and synthesis process. Despite the lack of justification behind the variable selection process of

the reviewed past studies, and the lack of evidence that the identification of factors was carried

out similarly, as there were limited past studies focusing on this topic, this method is commonly

adopted by researchers in various disciplines, For example, Jena (2014, p. 1) who conducted

analysis on the curriculum profile of management graduates, Hansen, Lee and Erika Di (2017)

who studied sustainable supply chains globally and Dada (2017) who modelled freeway

pedestrian crossing behaviour, all identified factors relevant to their analyses through literature

review.

In this study, after potential factors were identified through the literature review and synthesis,

a comparison of the potential factors driving share price movements, in general, and those of

REITs, specifically, was carried out. Subsequently, conclusions regarding the factors impacting

REIT share prices were drawn, however, only factors with controversial results from past

findings were put through to phase two, where their significance on, and relationship with M-

REIT share prices respectively were further investigated. Elements that set this apart from a

systematic review is that a systematic review is conducted based on a standard protocol which

is a more formal and rigid process for appraising literature and the past studies have to be

chosen by more than one reviewer (Kowalczyk & Truluck 2013, p. 220).

3.3.2 Quantitative and Non-Experimental Analysis

A quantitative relational and non-experimental research design was employed in this research,

to make statistical inferences about the REITs listed on Bursa Malaysia. A quantitative research

design was adopted because the research is concerned with quantifying the relationships

between independent variables and M-REIT share prices (dependent variable). This was

supported by Sousa, Driessnack and Mendes (2007, p. 503) who also asserted that quantitative

research designs are usually entrenched in the post-positivist paradigm. The approach is

objective and systematic in producing and processing knowledge. The research used deductive

reasoning, which is typically related to quantitative research designs. In deductive research, the


researcher convenes proofs to examine and test established theory or frameworks that have

been summarised into variables.

Moreover, quantitative research designs can be categorised as either experimental or non-

experimental (Research Methodology 2017). This research is non-experimental because the

purpose is to describe and examine the associations between variables through observation

without any random assignment, comparison or control groups or the manipulation of variables.

The research objectives of this study are to identify the firm-specific factors and

macroeconomic factors which affect M-REIT share prices, examine the relationship between

each of the analysed factors and M-REIT share prices and the effect of Shariah-compliance on

M-REIT share prices. BC Campus (n.d.) supported that a non-experimental research design is

more appropriate unless the research question is very distinctive about the causal relationship

between two variables. Also, a non-experimental research design should be adopted when it is

unethical and not feasible to carry out manipulation of the independent variables and random

allocation of participant variables to orders of conditions. In this study, the research questions

and hypotheses did not meet the criteria for experimental research design and they were built

on the relationships (non-causal relationships) between the independent and dependent

variables, hence, a non-experimental research design was apter. Under the non-experimental

design, the research adopted a predictive relational design. It investigated the nature of the

associations between independent and dependent variables systematically. The analysis also

included the magnitude, direction and strength of the relationships between the variables.

Predictive relational research uses the variance of independent variables to predict the variance

of one or more dependent variables (Sousa, Driessnack & Mendes 2007, p. 504).

3.3.3 Panel Data Analysis

The research adopted panel data analysis to determine the relationships between the dependent

and independent variables. A panel data regression model was more suitable for this study

because the data collected on the 17 REITs were longitudinal which indicated that it contained

multiple observations across multiple periods for the same REIT. In this research, EViews,

which is a contemporary econometric, statistical, analytic and forecasting software, was

adopted. The analysis was run through EViews software which is more user-friendly than the

other statistical packages suited for panel data, such as Stata and SAS (Statistical Analysis


System) (What is Eviews 2017). Also, as simple panel datasets were collected for this research,

statistical software packages that are dedicated to advance panel data, such as Stata were not

essential. Furthermore, the hypothesis testing that was carried out on EViews relied on four

fundamental steps which included stating the null and alternative hypotheses (refer to Para 3.5

Hypotheses), collecting and compiling the data for a test statistic to be formulated, which was

used to identify the p-value, followed by the interpretation of the p-value if certain data was

significant or not.

The independent variables first selected through the variable selection process were (1) market

capitalisation (MC), (2) dividend yield (DY); (3) price-earnings ratio (P/E ratio); (4) interest

rate (IR) and (5) inflation rate (IFR). Their respective relationships with the dependent variable,

the M-REIT share prices, were evaluated. Subsequently, Shariah-compliance was added as a

firm-specific factor to examine if compliance with sharia law had a significant impact on the

share prices. The independent variables were selected through the variable selection process as

demonstrated in the next subsection.

3.4 Variable Selection Criteria

Before moving on to the hypotheses, data collection and analysis, it is crucial to identify how

the variables in this analysis were selected. In a regression analysis, having a large pool of

candidate predictors can be a problem, because inessential predictors are likely to add noise to

the estimates of the analysis. When a variable is included in a regression model merely because

it is available instead of its relevance or significance, according to The Minitab Blog (2015),

the model acquires a low in degree of freedom and, therefore, is over-fitting. The Kellogg

School of Management (2017) stated that regressions which involve every possible predictor

variable are referred to kitchen sink regressions, which are likely to decrease the precision of

the regression analysis, leading to misleading outcomes. Therefore, it is crucial to select a

subset of predictors that can explain the observed relationships.

This subsection briefly demonstrates the process of selecting the variables for analysis, which

are potentially major drivers of REITs’ share price movements. The diagram below illustrates

the criteria and stages of selecting the independent variables.


Diagram 1: Variable Selection Criteria

Stage One Stage Two Stage Three

The first stage of the selection process was to identify the variables affecting share prices

analysed in previous studies. To avoid an over-fitting regression model, the variables were put

through to the second stage of the variable selection process, where the significance of the

relationships of the independent variables and the dependent variable (share price) found in the

analysis results of past studies were pointed out. The purpose was to eliminate the candidate

predictors based on the results of past analyses, which demonstrated that the inclusion of certain

variables may add little value to this study. At this stage, the variables analysed in past research

were categorised as variables that showed non-varying results and those with mixed results.

The variables that were unanimously concluded to be insignificantly related to the share price

movements by past studies were eliminated. At stage three, elimination was carried out based

on added value to the analysis, Therefore, all of the variables with non-varying results

demonstrated by the analyses in past studies were eliminated. Although varying outcomes from

past findings were signs that the relationship of an independent variable and the dependent

variable was worth investigating, its theoretical relevance was explored before including it in

the regression model. Throughout all of the three stages, a comparison between the variables

driving share price movements, in general, and the variables driving REIT share prices was

carried out as well.

The identification of factors through literature review and synthesis and the variable selection

process will be discussed in more detail in both Chapter Four: Results and Findings and

Chapter Five: Discussions.

Identification of the Variables

Analysed in Past Studies

Elimination based on the

Significance of the Variables

Analysed

Elimination based on

Added-Value to the Analysis


3.5 Hypotheses

Based on the results shown in past studies and the identification of independent variables that

would be analysed through the variable selection process, hypotheses were constructed,

connecting underlying theories and the research questions.

H1: There is a positive relationship between the market capitalisation (MC) of an M-REIT and

its share price.

H2: There is a positive relationship between the dividend yield (DY) of an M-REIT and its

share price.

H3: There is no positive relationship between the price-earnings ratio (P/E ratio) of an M-REIT

and its share price.

H4: There is no positive relationship between the interest rate (IR) and M-REIT share prices.

H5: There is no positive relationship between the inflation rate (IFR) and M-REIT share prices.

H6: There is a positive relationship between Shariah-compliance, as a firm-specific factor, and

M-REIT share prices.

3.6 Conceptual Framework

The conceptual framework of a study is the system of concepts, assumptions, beliefs and

theories which form the foundation of the research, and explain the main concepts and factors

or variables to be analysed (Jabereen 2009, p. 49). Instead of providing merely theoretical

clarification, a conceptual framework offers interpretations and understanding and can be

originated from the process of both quantitative and qualitative analysis (Jabereen 2009, p. 49).

Diagram 2 shows the conceptual framework applied to this research.


Diagram 2: Conceptual Framework

Independent Variables

Dependent Variable

It was believed that market capitalisation (MC), dividend yield (DY), the price-earnings ratio

(P/E ratio), interest rate (IR), inflation rate (IFR) and Shariah-compliance significantly affected

the share price movements of REITs listed on Bursa Malaysia, known as M-REITs. The

presumed relationship between an M-REIT’s MC and its share price was positive because, in

the perception of investors, in general, a greater MC denotes that an organisation can provide

better quality goods and services and attain superior performance (Merrill Edge 2017;

Market Capitalisation (MC)

Dividend Yield (DY)

Price-Earnings ratio (P/E ratio)

Interest Rate (IR)

Inflation Rate (IFR)

M-REIT Share Prices

H2

H3

H4

Shariah-Compliance

H5

H1

H6


Mladjenovic 2017). It is also expected to have less potential for significant growth, but steadier

growth than a small-cap organisation. Therefore, the presumed relationship between the MC

and share price of an M-REIT was explained by the investors’ risk and uncertainty profile in

Malaysia in general, which is claimed to be prone to risk and uncertainty avoidance (Ung 2012;

Rao 2019). The relationship between the DY and the M-REIT’s share price was also presumed

to be positive because the DY is a direct indication of the earnings from an investment made

by an existing shareholder (Anspach 2019). Conceptually, when a firm issues a higher than

expected dividend payment, market sentiment tends to shift and an upward movement of the

share price is anticipated (Scottrade 2014).

On the other hand, when an organisation’s price-earnings ratio (P/E ratio) rises, its share price

is expected to fall. This is because, in theory, investors anticipate higher returns from investing

in an organisation with a high P/E ratio, and it is likely for the share price of such an

organisation to be overvalued (Murphy 2019). This denotes that investors of the shares carry a

higher risk of losing their investments if the higher earnings expectations are not eventually

met. Contrarily, a low P/E ratio may indicate that the share price of the organisation is

undervalued, or its performance is exceptionally outstanding, as compared to its historic trends

(Murphy 2019). Thus, when the share price is undervalued, it is likely to rise soon. Therefore,

conceptually the P/E ratio has an inverse relationship with share price movements and the same

was presumed for M-REITs.

If Shariah-compliance is also treated as a firm-specific factor, it is expected to affect M-REIT

share prices positively. This is because Shariah-compliant organisations are perceived as more

favourable financial vehicles, which avail a lower risk-return ratio and the fact that their

monetary value of financial solvency is invariably supported by an equal value asset (Kuwait

Finance House 2011). A higher resilience against volatility or shocks is an expected attribute

of Shariah-compliant organisations, in general. Shariah-compliant M-REITs’ superior

performance, as compared to conventional M-REITs or other stocks, through the 2008 GFC

strengthened such presumptions (Newell & Osmadi 2009, p. 239).


For both of the macroeconomic factors, the interest rate (IR) and the inflation rate (IFR), their

relationships with M-REIT share prices were presumed to be negative. Harper (2009) and Kaur

(2017) stated that a rising IR climate is typically perceived to lead to falling share prices. This

is because a higher IR signifies the cost of debt for REITs will increase and, thus, it will become

more challenging to realise profitable growth (Gupta 2017; Warden 2018). Also, REITs are

high-yield investment vehicles because 90 per cent of a REIT’s taxable profit has to be

distributed in the form of dividends to its investors (Harper 2009). Thus, REITs are also

typically expected to be sensitive to IR fluctuations. Whereas, the IFR was presumed to be

negatively related to share prices because the purchasing power of currencies declines when

the IFR rises, which also causes the economy to decelerate until the IFR is stabilised (Zucchi

2017). This presumption is also attributable to the expected surge of fears among investors in

an inflationary environment when the purchasing power of the country’s currency erodes

(Mowell 2013).

The conceptual framework formed a foundation for the analysis of this research. There are

more discussions on the theoretical relevance of the relationships of these variables and the M-

REIT share prices and conflicting theories in Chapter Five: Discussions. In the next subsection,

data collection, and the limitations of data collection will be discussed.

3.7 Data Collection

3.7.1 Secondary Data and Data Source

Firm-specific data concerning the M-REITs and macroeconomic data were needed to

investigate their relationships with the dependent variable. The data were readily available from

secondary sources, such as the M-REITs and government sources, for example, Bursa Malaysia.

Therefore, secondary data, which are often administrative data, where data collection is

typically routine and can cover a long period, enabling the detection of changes over time, were

collected (Institute for Work & Health 2015). Furthermore, secondary data are readily available

and, hence, less expensive to obtain and freely accessible. This is widely supported by past

studies where secondary data have been collected to analyse the impacts of selected

independent variables on the dependent variable. There have been a few past studies which

have adopted primary data analysis or a mix of both primary and secondary data, for example,


Allahawiah and Amro (2012, pp. 236-245) and Salam, Islam and Hasan (2015, pp. 15-33).

Questionnaires were distributed among senior management teams, financial brokers and

different personnel of the companies that were analysed. The authors believed that they could

provide professional opinions on the factors driving share price movements. The usage of

questionnaires in such research has been critically critiqued because people’s opinions are

subjective and when the factors affecting a company’s share price are founded on people’s

opinions, they are deemed to be biased (Laerd Dissertation 2012). Furthermore, this research

was built on quantitative analysis and as the secondary financial data regarding the variables

were typically available to the public, there was no need for primary data collection. Also,

primary data, which are data collected first hand, were not possible due to access, time and cost

constraints (Foley 2018).

Secondary data on M-REIT share prices and the potential variables that influenced share price

movements were sourced mainly from the Stock Exchange of Malaysia (Bursa Malaysia)

databases, M-REITs’ annual reports and other websites, such as Trading Economics. The

financial data of the firm-specific variables were retrieved from annual reports of the respective

M-REITs and the web page of Bursa Malaysia while the data on the macroeconomic variables

were retrieved from the web page of Trading Economics.

3.7.2 Sample Selection and Limitations

In this research, 17 REITs listed on Bursa Malaysia were studied. The data source spanned

from 2008 to 2017 (10 years), but for the M-REITs that were established after the year 2008,

data was compiled from their inauguration. Data validity and reliability were ensured by

collecting information only from official sources (Gatua 2013). According to Hurlin (2010),

Katchova (2013) and Moffatt (2017), panel data, which is also known as longitudinal data, is

where the same units are observed in different periods. It is defined as unbalanced when each

entity in a dataset contains dissimilar numbers of observations. Therefore, the data collected

for this research were unbalanced panel data.

According to Do (2011) and Williams (2018), studies will result in bias estimation if missing

data is ignored and if the researchers choose to include only entities that remain in all of the


periods. Hence, the initial plan was to include the entire population of M-REITs. 17 out of 18

M-REITs were still included in the observations, despite the unbalanced nature of the dataset

except for the KIP REIT, a retail REIT which was newly established and listed on Bursa

Malaysia in 2017. The exclusion of the KIP REIT was due to the non-availability of

information on the REIT when the research and analyses were carried out. This constituted the

limitation of the sample size. The unbalanced nature of the panel dataset will be discussed

further in the next subsection.

3.8 Data Analysis

As mentioned, panel data analysis was adopted to determine the relationships between the

dependent variable (M-REIT share prices) and the independent variables while the magnitude

of change in the M-REIT share prices was analysed. Hurlin (2010), Katchova (2013) and

Moffatt (2017) stated that panel data which is also known as longitudinal or cross-sectional

data is multidimensional and involves measurements over time. Thus, panel data analysis

provides multiple observations over time. According to Mayer (2010) and Katchova (2013),

unbalanced panel data is a dataset where certain years of a certain data category are not

observed. Among the 17 REITs analysed, some were established after the year 2008 which

indicated that some of the REITs were not observed in all of the periods. Therefore, the panel

data in this research was unbalanced.

According to Do (2011) and Williams (2018), balancing the data through the exclusion of the

data of all of the entities that did not remain in all of the periods might lead to bias in the data

construction. Williams (2018) stated that by dropping the subjects, which is also referred to as

listwise or casewise deletion, may cause the remaining samples to be unrepresentative of the

total population, especially, when the study involves a small population. However, the authors

also stated that it is detrimental to just ignore the fact that the data is unbalanced, hence, it is

crucial to identify the reason for missing data and missing patterns in the panel dataset. The

nature of the unbalanced data of the 17 M-REITs observed in this research was not random,

and generalising the data was not possible because it was not the case of missing values, but

rather non-existent data, as some of the M-REITs were established post-2008. Nevertheless,

according to Baltagi (2005, p. 165), Cameron and Trivedi (2010, p. 91) and Williams (2018),


unbalanced panel data only becomes a problem when the additional disturbance resulting from

the unbalanced data is significant.

In the simplest form, the panel data equation is made up of:

(1) Y = a + bX + u

Where:

a represents Y-intercept,

b represents the slope,

and u represents the error term.

Furthermore, for a balanced panel dataset, the error term is written as:

(2) u = mu + v

Where:

mu represents the mean of the random error distribution,

and v represents the random error.

Whereas, for an unbalanced panel dataset, an additional error term is present in “u”, hence:

(3) u = mu + v + e

Where:

“e” represents the additional disturbance caused by the unbalanced nature of the dataset.

Baltagi (2005, p. 165), Cameron and Trivedi (2010, p. 91) and Williams (2018) stated that

unbalanced panel data arises as an issue only when the significance of the value of “e” is high,

hence, escalating the error term for the panel data model. To estimate the value of “e” (the

additional disturbance), ANOVA (Analysis of Variance), MIVQUE (Minimum Variance


Quadratic Unbiased Estimation) and MLE (Maximum Likelihood Estimation) can be adopted

which each have their strengths and weaknesses or biases (Swallow & Monahan 1984, p. 47;

Baltagi 2005, p. 165). ANOVA (Analysis of Variance) could typically be adopted to calculate

the additional disturbance occurring in the unbalanced dataset. Swallow and Monahan (1984,

p. 47) and Baltagi (2005, p. 165) claimed that ANOVA is a measure no less superior than the

more complicated MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and MLE

(Maximum Likelihood Estimation).

However, for this research, the additional disturbance was not calculated because the

unbalanced panel data was not a case of missing values, but rather the data never existed.

Therefore, the assumption was made that independence across the cross-sectional units would

function similarly regardless of the nature of the data, balanced or unbalanced (Berkeley

University of California 2018).

Reyna (2007) and Katchova (2013) also claimed that in panel data, the assumption includes

that unobserved heterogeneity exists across individuals and it can be captured by αi. For this

research, it was assumed that the individual-specific effects αi were related to the independent

variables. Therefore, a fixed-effect (FE) model should be adopted. When all of the necessary

data had been gathered, EViews was run to perform the statistical analysis. The equation of the

FE model for determining the association between the dependent and independent variables is:

Yit = β1Xit + αi + uit

Where:

αi (i = 1….n) is the unknown intercept for each entity (n entity-specific intercepts),

Yit is the dependent variable (DV) where i = entity and t = time,

Xit represents one independent variable (IV),

β1 is the coefficient for that IV,

and uit is the error term.


According to Katchova (2013), independent variables or regressors (Xit) that are varying (vary

by both individuals and time) and individual invariant regressors (Xit = Xt for all of the i, they

do not change across the individuals) should not be placed in the same regression model unless

measures are taken to link firm-specific and macroeconomic data. This is supported by The

University of Manchester (2017) which stated that to combine firm-specific or microeconomic

and macroeconomic data, a variable must be generated to connect the two datasets. It is known

as a macro unit identifier. However, for this research, a macro unit identifier was not created

and, therefore, the firm-specific and macroeconomic independent variables identified in the

previous subsections were placed in two different regression models.

The model for determining the association between the dependent variable and varying

regressors (firm-specific independent variables) is:

SPit = β1MCit + β2DYit + β3PERit + αi + uit

Where:

αi (i = 1….n) is the unknown intercept for each entity (n entity-specific intercepts).

SPit is the Share Price (the dependent variable) of stock i at time t.

MCit represents the Market Capitalisation of stock i at time t.

DYit represents the Dividend Yield of stock i at time t.

PERit represents the Price-earnings Ratio of stock i at time t.

β1-3 are the coefficients to be estimated or the coefficients of the slope parameters.

uit is the error term.

On the other hand, the model for determining the association between the dependent variable

and individual invariant regressors (macroeconomic independent variables) is:


SPit = β1IRt + β2IFRt + αi + uit

Where:



IRt represents the Interest Rate at time t.

IFRt represents the Inflation Rate at time t.



Also, the impacts of Shariah-compliance on M-REIT share prices were also analysed. A

dummy variable was created to signal if an M-REIT was a conventional or a Shariah-compliant

M-REIT. The conventional M-REITs were given the value of zero (“0”) while Shariah-

compliant M-REITs were given the value of one (“1”). This is consistent with Farooq and

Alahkam (2016) who also adopted a dummy variable to indicate if the respective organisation

analysed in their study was conventional or Shariah-compliant when they examined the impacts

of Shariah-compliance on non-financial organisations in MENA stock markets.

The basic model to evaluate the Shariah-compliance effects was constructed as follows:

SPit = β1SCit + αi + uit

Where:



SCit represents the status of the M-REIT whether it is Shariah-compliant or

conventional.



By taking into consideration other firm-specific factors that have been selected as the regressors,

the regression equation is as follows:

SPit = β1SCit + β2MCit + β3DYit + β4PERit + αi + uit

Where:



SCit represents the status of the M-REIT whether it is Shariah-compliant or conventional.

MCit represents the Market Capitalisation of stock i at time t.

DYit represents the Dividend Yield of stock i at time t.

PERit represents the Price-earnings Ratio of stock i at time t.



3.9 Summary

In this chapter, the research methodology adopted for this study has been discussed in detail.

This included the research philosophy, research framework, hypotheses, conceptual framework

and the data analysis which built the backbone of this study. It has given a preview into the two

phases of the research designed to answer the research questions. Regression models that were

adopted to analyse the impacts of the independent variables on the M-REIT share prices were

illustrated as well. Besides, the limitations of sample size and data collection were scrutinised.

Although the additional disturbances caused by the unbalanced panel data (due to the M-REITs

established post-2008) were claimed to be trivial and, therefore, not calculated, measures to

rectify the additional disturbances were mildly explored which might be of value for

researchers who study this topic in the future. The next chapter will present the findings of the

data analysis.


CHAPTER FOUR RESULTS AND FINDINGS

4.1 Introduction

This chapter explains the results of the two phases of the study in detail. Phase one of the study

was the unconventional way of identifying factors through literature review and synthesis.

Phase two of the study was the data analysis which was run through EViews to examine the

relationships between the selected independent variables and the M-REIT share prices.

4.2 Phase One: Identification of Factors through Literature Review and Synthesis

In this subsection, the factors driving share price movements, in general, and those of REITs

identified in the past studies were studied and compared. The illustration of the variable

selection process also showed the rationale behind the independent variables chosen.

24 independent variables were analysed in the past studies reviewed, of which 18 of them were

firm-specific variables while six of them were macroeconomic variables. Past studies which

concentrated on the factors affecting share prices, in general, carried out their analyses on 16

firm-specific and six macroeconomic independent variables. On the contrary, the past studies

focusing on factors driving REIT share prices were more limited and only the relationships of

seven firm-specific and two macroeconomic independent variables with REIT share prices

were explored.

The findings through the literature review and synthesis concluded that the factors significantly

related to a company’s share price movements, in general, were the company’s market

capitalisation (MC), dividend yield (DY), book value (BV) or net asset value (NAV), return on

equity (ROE), return on assets (ROA), debt to asset ratio (D/A Ratio), economic value added

(EVA), leverage (represented by the debt to capital ratio), first lag of the share price, interest

rate (IR) and exchange rate (ER). As for the price-earnings ratio (P/E Ratio), earnings per share

(EPS), dividend per share (DPS), Shariah-compliance, the inflation rate (IFR) and money


supply, some past studies claimed that they were of great influence over share price movements

but some analysis results varied, hence, further investigation was prompted.

On the other hand, in the REIT market, MC, NAV, the debt to equity ratio (D/E ratio), the D/A

ratio, DY and IFR were deduced to be significantly related to REIT share prices while there

were contradicting results drawn from the findings of past studies concerning the relationship

between the IR and REIT share prices. As for net income (NI), the result showed that it had

little influence over share prices.

The findings of the literature review and synthesis process will be outlined in-depth in the next

subsection, as the independent variables selection process is illustrated,

4.3 Variable Selection Process

As mentioned in Para 3.4 Variable Selection Criteria, the inclusion of a large pool of candidate

predictors in a regression analysis could increase noise to the analysis estimates (The Minitab

Blog 2015). This study aimed to avoid an over-fitting regression and predictor variables which

would have added no value to the analysis. Therefore, the variable selection process was

precisely carried out.

4.3.1 Stage One: Identification of Variables Analysed in Past Studies

The first stage of the selection process was to identify the variables affecting share prices that

were analysed in previous studies. There were 24 variables identified at this stage,

encompassing 18 firm-specific and six macroeconomic factors. The firm-specific factors

identified in past studies which aimed to investigate the factors driving share prices in general,

as well as those in the REIT markets were MC, NAV, D/A ratio, DY and Shariah-compliance,

whereas, for macroeconomic factors, IR and IFR. D/E ratio and NI were only analysed by past

research studying REIT share price movements. On the other hand, EPS, the P/E ratio, RE,

DPS, DPR, ROE, ROA, EVA, leverage (represented by the debt to capital ratio), the first lag

of the share price and size (represented by the logarithms of total assets) were firm-specific

independent variables identified only in past studies focusing on the factors driving share prices,


in general, while the macroeconomic factors identified, in general, were ER, money supply,

crude oil price and the gross domestic product (GDP).

To avoid an over-fitting regression model, the variables mentioned were put through to the

second stage of the variable selection process, where the significance of the relationships of

the independent variables and the dependent variable (share price) found in the analysis results

of past studies was pointed out.

4.3.2 Stage Two: Elimination based on Significance of Variables Analysed

At the second stage of the variable selection process, the significance of the various variables

was studied through the findings of past studies. The purpose was to eliminate the candidate

predictors based on the results of past analyses which demonstrated that the inclusion of certain

variables may add little value to this study. The variables were categorised as variables that

showed non-varying results and those with mixed results.

(a) Non-Varying Results

This subsection illustrates the relationships of certain predictors with share prices where the

results concluded in past studies were similar.

(i) Significant Relationship

All of the past studies that included NAV, ER, the D/E ratio, ROE, the D/A ratio, ROA, EVA,

the debt to capital ratio and the first lag of the share price in their regression model claimed

that these variables were significantly related to share prices. According to Avdalovic (2018,

p. 19) and some other past studies 1, there was a significant and positive relationship between

NAV and share prices in general. On the other hand, Ying (2004) and other past studies 2 agreed

that the relationship of NAV and share prices was significant and positive in the REIT market

1 Malhotra, Chandiwala and Tandon (2013, p. 94), Geetha and Swaaminathan (2015, p. 109), Sharif, Purohit and Pillai (2015, p. 213), Kodithuwakku (2016, p. 76) and Aveh and Vitor (2017)

2 Clayton and MacKinnon (2000), Brent et al. (2011, p. 41), Ong, Teh and Chong (2011, p. 13), Mohammad and Zolkifli (2013) and Olanrele (2014, p. 500)


as well. Furthermore, Adam and Tweneboah (2008) and Aroni (2011, p. 310) are past studies

that investigated the effects of the ER on share prices and their findings showed a significant

but negative relationship between the two variables in general.

As for the D/E ratio, only Strange and Tang (2000) studied its impacts on REIT share prices.

The analysis showed that the D/E ratio was significantly and negatively related to REIT share

prices. Furthermore, the analysis showed a negative and significant relationship between the

D/A ratio and share prices in the REIT market which was supported by Sharif, Purohit and

Pillai (2015, p. 213) which focused on the factors driving share price movements in general.

Also, Sharif, Purohit and Pillai (2015, p. 214) and Aveh and Vitor (2017) analysed the impacts

of the ROE on share prices, in general, and the results were found to be positive and significant.

Similarly, Avdalovic (2018, p. 19) deduced that there was a significantly positive relationship

between the ROA and share price movements while Nautiyal and Kavidayal (2018, p. 707)’s

findings demonstrated the same between the EVA and share price movements. Singh (2018)

concluded that the debt to capital ratio and the first lag of share price would influence share

prices positively and significantly. They were the variables that only occurred once in past

studies.

(ii) Insignificant Relationship

All of the past studies which have analysed the effects of NI 1, RE 2, DPR 3, size (represented

by the logarithms of total assets) 4, crude oil price 5 and GDP 6 concluded that their relationships

1 Mohammad and Zolkifli (2013) and Olanrele (2014, p. 500)

2 Khan (2009)

3 Malhotra, Chandiwala and Tandon (2013, p. 94) and Singh (2018)

4 Singh (2018)

5 Heng et al. (2012)

6 Barasa (2014) and Singh (2018)


with the share price were insignificant. Therefore, these variables were eliminated directly at

this stage.

(b) Mixed Results

On the contrary, there were conflicting results from past studies concerning the relationships

between some variables and the share price, be it, in general, or in the REIT market. This is

illustrated in the following subsections.

(i) Relationship with Similar Strength but Varying Directions

This subsection shows the independent variables where the strength or significance of their

relationships with the share price was concluded to be similar through past studies. However,

the variable was found to be either positively or negatively related to share prices in various

past studies. The only variable which fell under this category was market capitalisation (MC).

According to Ali (2006) and some other past studies 1, MC had a positive relationship with

REITs’ share price movements and the relationship was significant. This was supported by the

findings of Avdalovic (2018, p. 19) and other past studies 2 which stated that the MC of an

organisation, in general, significantly and positively drove its share price in the same direction.

However, Strange and Tang (2000) found that the MC had significant but negative impacts on

REIT share prices.

(ii) Relationship with Varying Strengths and Directions

The past studies also showed conflicting results on some variables, both in terms of the strength

of their relationships with the share price, as well as the direction (positive or negative) of the

relationships. This is illustrated in the following subsection.

1 Ziering, Liang and McIntosh (1999, p. 65), Conover, Friday and Howton (2000, p. 162), Below,

Stansell and Coffin (2000, p. 277), Clayton and MacKinnon (2000), Mohammad and Zolkifli (2013)

and Olanrele (2014, p. 500)

2 Allahawiah and Amro (2012, p. 239), Sharif, Purohit and Pillai (2015, p. 213) and Aveh and Vitor

(2017)


Singh (2018) and other past research 1 stated that the EPS was significantly and positively

related to share price movements. Contrarily, Sharif, Purohit and Pillai (2015, p. 214) deduced

that the EPS was inversely related to share prices but the relationship was insignificant. This

was agreed by Nautiyal and Kavidayal (2018, p. 707). They claimed that investors do not make

their investment decisions based on the EPS because the EPS also tends to increase when stock

repurchases are greater in amount, instead of being influenced just by stronger profit.

According to Malhotra, Chandiwala and Tandon (2013, p. 94), Sharif, Purohit and Pillai (2015,

p. 213) and Geetha and Swaaminathan (2015, p. 109), an organisation’s P/E ratio has

significant and positive impacts on its share price. However, this was rebutted by Khan (2009)

who claimed that other variables, such as the DY and RE (which were claimed to be

insignificantly related to share price) explained the share price movements better than the P/E

ratio. Thus, according to the author, the P/E ratio had an insignificant influence on share prices

and this was supported by Singh (2018).

Moreover, Sharif, Purohit and Pillai (2015, p. 213) and Kodithuwakku (2016, p. 76)’s findings

demonstrated a significant and positive relationship between the DPS and share price

movements while Malhotra, Chandiwala and Tandon (2013, p. 94) and Geetha and

Swaaminathan (2015, p. 109) agreed that the relationship was positive but insignificant.

Contrarily, Nautiyal and Kavidayal (2018, p. 707) found that share prices were significantly

and negatively influenced by the DPS.

Similarly, past researchers have found varying results of the relationship between the DY and

share price movements. Strange and Tang (2000) and Mohammad and Zolkifli (2013)

concluded that the DY of a REIT would positively and significantly affect its share price. Khan

(2009), who analysed the factors, in general, agreed with the findings. On the contrary,

Malhotra, Chandiwala and Tandon (2013, p. 94) and Sharif, Purohit and Pillai (2015, p. 213)’s

findings showed that the DY’s impact on an organisation’s share price was significant, but they

1 Malhotra, Chandiwala and Tandon (2013, p. 94), Geetha and Swaaminathan (2015, p. 109), Salam,

Islam and Hasan (2015, p. 15), Kodithuwakku (2016, p. 76) and Aveh and Vitor (2017)


were negatively related while Aveh and Vitor (2017) claimed that the impact was insignificant.

Also, past studies, such as Mohamad (2015) and Foo and Muhammad (2015) asserted a positive

and significant relationship between a REIT’s Shariah-compliance status and its share price,

while Yazi, Morni and Song (2015, p. 1019) and Mohamed and Lusyana (2017, p. 21) claimed

that Shariah-compliant stocks, in general, had superior share prices or returns to conventional

ones. On the contrary, Reddy and Fu (2014) and Farooq and Alahkam (2016) refuted,

concluding that Shariah-compliant stocks provided less favourable returns. Differently from

past studies investigating the impacts of Shariah-compliance on share price movements, Morad

and Masih (2015) compared the reactions of Shariah-compliant REITs and conventional REITs

against the macroeconomic indicators, namely; the IR and IFR and found that whether a REIT

complied to Sharia law, or not, was of little significance.

As for the relationship between the money supply and an organisation’s share price, it was

deduced to be significantly positive by Naik and Padhi (2012, p. 36) and Heng et al. (2012),

whereas, Sirucek (2012, p. 399) stated that they were negatively and significantly related.

Refutably, Aroni (2011, p. 310), Khan and Zaman (2012) and Barasa (2014) claimed that the

relationship between the two variables was positive but insignificant. Fang et al. (2016, p. 245)

and some other past studies 1 concluded that the IFR could impact share prices negatively and

significantly, but this was rebutted by Khan and Zaman (2012) and Barasa (2014)’s findings,

deducing that the relationship was insignificant. Nevertheless, Adam and Tweneboah (2008)

and Aroni (2011, p. 310)’s analyses demonstrated a positive but insignificant relationship

between the two variables. No other past research focusing on the factors driving the share

price movements of REITs included the IFR as an independent variable in their analysis except

Fang et al. (2016, pp. 244-245). Taking all of the past studies into consideration, the varying

results might be signs that the impacts of the IFR on REIT share prices should be further

explored.

1 Naik and Padhi (2012, p. 36), Heng et al. (2012), Hussein (2017) and Singh (2018)


Besides, Cheong et al. (2006), Hooi and Smyth (2011), Ito (2013) and Fang et al. (2016, p.

244-245) concluded that the IR was negatively related to the share price movements of REITs

but the impacts were significant. Adam and Tweneboah (2008), Aroni (2011, p. 310) and Heng

et al. (2012) supported that IR and share price movements, in general, were negatively related.

All of the past studies consistently proved a negative and significant relationship between the

two variables, except for Wong (2015) and Diedrich (2017) who claimed that the IR had little

influence over REITs’ share price movements.

At this stage of the variable selection process, the significance of the relationships of the

independent variables with the dependent variable was used as the basis of elimination.

Therefore, six independent variables, namely; NI, RE, DPR, size (represented by the logarithms

of total assets), the crude oil price and the GDP were eliminated from the panel data regression

model as all of the past studies agreed that their effects on share price movements were

insignificant.

4.3.3 Stage Three: Elimination based on Added-Value to the Analysis

Among the 18 variables remaining, subsequent to the stage two elimination process, nine

variables, namely; NAV, ROE, ROA, EVA, leverage (represented by the debt to capital ratio)

and the first lag of the share price were unanimously found to be significantly and positively

related to share price movements, whereas, the ER and the D/E and D/A ratios impacted the

share price movements inversely and significantly. There was no differing outcome from the

past studies which, thus, provided less reason to investigate if the variables were highly related

to share prices because the significance was already profoundly proven. Therefore, in this study,

NAV, ROE, ER, the D/E ratio, the D/A ratio, ROA, EVA, the debt to capital ratio and the first

lag of the share price were excluded from the regression model. Contrarily, despite there being

merely two past studies which claimed that the IR’s relationship with share prices was

insignificant among all of the past research declaring a significant and negative relationship

between the two, the IR was still considered as one of the predictor variables. This was not

only because its influence on share prices, especially, in the REIT industry is pivotal, it was

also because there was conflicting theoretical reasoning regarding the relationship between the

IR and share prices.


On the other hand, past research findings indicated varying results on the impacts of market

capitalisation (MC), DY, DPS, EPS, P/E ratio, Shariah-compliance, IFR and the money supply

on share prices. According to the Kellogg School of Management (2017), the most crucial

consideration during the variable selection process is the theoretical relevance of a variable.

Thus, although varying outcomes from past findings were signs that the relationship of an

independent variable and the dependent variable was worth investigating, its theoretical

relevance was explored before including it in the regression model.

(a) Market Capitalisation (MC)

Market capitalisation (MC) represents the relative size of an organisation to another (The

Economist 2006). According to Mladjenovic (2017), MC measures an organisation’s value on

the open market and is regarded as the market’s perception of its prospects because it signifies

what investors are willing to pay for the organisation’s shares. Fidelity (2017) and Merrill Edge

(2017) claimed that generally, in the eyes of investors, an organisation with greater MC

indicates that it offers better quality goods and services, consistent dividend payments and

steady growth, thus, dominating established industries. Therefore, investing in such an

organisation’s shares is considered a more conservative investment decision than those with a

lower capitalisation. According to the authors, it offers less risk for possibly less aggressive

growth potential, thus, attracting risk-averse investors. MC is generally regarded as positively

related to share price movements.

Theoretically, MC is considered as one of the major factors that significantly and positively

drive the share prices of REITs. However, Strange and Tang (2000) concluded that MC has

significant but negative impacts on a REIT’s share price. The theoretical relevance for such an

argument was that firms with smaller MC usually serve niche markets or emerging industries,

have relatively limited resources and can be more susceptible to an economic downturn, but

can provide significant growth potential to long-term investors who can tolerate volatile stock

price swings in the short-term (Mladjenovic 2017; Fidelity 2017; Merrill Edge 2017). This

indicates that such organisations attract risk-seeking investors. Therefore, whether MC is

positively or negatively related to share price movements will not only depend on the market

or industry being analysed, it will depend also on the behaviours of investors based on the

geographical focus of the research. In a nutshell, it is crucial to investigate the relationship


between the MC of a REIT listed in Malaysia and its share price movements by including it as

a predictor in the regression model.

(b) Dividend per Share (DPS) Versus Dividend Yield (DY)

A dividend is the share of earnings an organisation pays to shareholders in return for their

investment. According to Scottrade (2014), when a firm issues a higher than expected dividend

payment, market sentiment tends to shift and this is expected to cause an upward movement of

the share price. On the contrary, Chen (2017) stated that for mutual funds, similar to REITs,

the share price will drop to offset the payout, thus, the DPS or DY can be negatively related to

share price movements. The DY is calculated by dividing the DPS with the market price per

share. As it is presented as a percentage, rather than as a dollar amount like the DPS, it is easier

to see the return per dollar invested that shareholders receive through dividends. Moreover, the

DY does not only take into consideration the dividend payment and the number of shares

outstanding but also the market value of the share.

The past studies indicated that the DPS was positively related to the share price movements but

they did not agree on its significance as a predictor variable. On the other hand, the past

research findings all supported that the DY impacted share prices significantly, but the

relationship could be either positive or negative. This is in line with the theoretical explanation

above. Taking into account both the theory and the findings of past research, the DY seemed

to be a better predictor of share price movements. Therefore, the DY was included in the

analysis.

(c) Earnings per Share (EPS) Versus Price-Earnings Ratio (P/E Ratio)

The earnings per share (EPS) represents a company's net earnings divided by the total number

of shares outstanding (Fedorov 2017). Islam et al. (2014, pp. 97-108) claimed that the EPS was

predominantly regarded as one of the most crucial factors in determining the share price and a

firm’s value. According to the authors, large numbers of individual investors have made

investment decisions based on an organisation’s EPS. This was supported by Fedorov (2017)

stating that, in theory, the relationship between the EPS and share prices is positive. However,

this was rebutted by Sharif, Purohit and Pillai (2015, p. 213) who deduced that the EPS was


inversely related to the share price, although the relationship was insignificant. They claimed

that investors do not make their investment decisions based on the EPS because the EPS also

increases when stock repurchases are greater in amount instead of being influenced by only a

stronger profit. Based on these conflicting theories, there is a need to investigate how REITs’

share prices in Malaysia are affected by their EPS.

On the other hand, according to The Motley Fool (2017), the price-earnings ratio (P/E ratio)

measures the relationship between an organisation's share price and its EPS. It is calculated by

dividing the organisation’s current share price by its EPS. Theoretically, Murphy (2018) stated

that investors anticipate higher earnings growth prospects from organisations that have a higher

P/E ratio than those with a lower P/E. It is likely for the share price of an organisation with a

high P/E ratio to be overvalued. This indicates that investors of such a stock bear more risk of

losing their investments if the higher earnings expectations are not eventually met. Contrarily,

a low P/E ratio may mean that the organisation’s share price is undervalued or its performance

is exceptionally outstanding in comparison with its historic trends. The P/E ratio is the price an

investor is paying for $1 of an organisation's earnings or profit. When the share price is

undervalued, it is likely to rise soon. Therefore, the P/E ratio, in general, has an inverse

relationship with share price movements. Inconsistent with theory, the majority of past research

has concluded that the P/E ratio was significantly and positively related to share price

movements, except for Khan (2009) and Singh (2018) who claimed that the impacts of the P/E

ratio on share prices were insignificant. Hence, taking into consideration the importance of the

P/E ratio to investors, in theory, it is crucial to find out if it truly has a significant relationship

with the share price movements of REITs in Malaysia, and whether the relationship is positive

or negative.

However, being the denominator of the P/E ratio, the EPS is a direct factor that influences the

P/E ratio (Huang 2008). Therefore, by including both the EPS and the P/E ratio in the regression

model, the problem of multicollinearity is likely to occur, which is a phenomenon where, in a

regression model, there are two or more predictor variables that are moderately or highly

correlated (Frost 2018). According to The Minitab Blog (2015) and Frost (2018),

multicollinearity weakens the statistical power of analysis because it reduces the precision and

stability of the coefficient estimates, leading to more difficult interpretation. Hence, it is crucial


to minimise multicollinearity in an analysis. According to the authors, one of the most direct

methods to minimise the problem of multicollinearity is by removing one or more independent

variables that are highly correlated from the regression model. According to Picardo (2017),

the EPS does not reveal much to investors about the worth of investing in a certain stock

because the share price is not factored in while the P/E ratio takes into account not only a firm’s

past performance but also the market expectations of the firm’s growth. This indicates that the

P/E ratio is a better predictor of what to expect in the future and how the share price will tend

to shift as compared to the EPS. Therefore, to minimise the problem of multicollinearity, the

P/E ratio was included in the regression model, while the EPS was removed.

(d) Money Supply

The past findings agreed that the relationship between the money supply and share prices was

positive but only Naik and Padhi (2012, p. 36) and Heng et al. (2012) claimed that it was

significant. Although the money supply was not an independent variable that was selected in

past studies which concentrated on the factors driving share prices in REIT markets, the

controversy over its impacts on share prices, in general, should not be ignored. Therefore, its

theoretical relevance was still looked into so that the variable selection process would be more

objective.

Sellin (2001) argued that share prices are majorly driven by the money supply, only when

changes in the money supply alters anticipation about future monetary policy. According to the

author, investors tend to expect future monetary policy to tighten when there has been an

increase in the money supply. On the contrary, Bernanke and Kuttner (2004) claimed that the

impacts of the money supply on share price movements were driven by its effect on the

perceived risk, and the monetary value of the shares. Due to the impacts of the money supply

on the IR, it affects the shares’ monetary value as well. The authors believed that tightening

monetary policy would cause the real IR to rise, followed by an increase in the discount rate

which would cause share prices to fall. There have been several conflicting theories concerning

the impacts of the money supply on share price movements. Karim (2013, p. 1068), Tan (2014)

and MIDF Research (2017) asserted that there had only been minor fluctuations over the years

in terms of the Malaysian IR because of the IR targeting or benchmarking set by the central

bank. The authors also affirmed that the amount of money injected into the economy, or the


money supply growth rate in Malaysia, had been strongly related to their IR targeting.

Therefore, to avoid multicollinearity, the money supply was not included as an independent

variable in the regression model.

(e) Inflation Rate (IFR)

According to Zucchi (2017), the purchasing power of a currency declines when inflation rises,

which also causes the economy to decelerate until the inflation rate (IFR) is stabilised. The

author also stated that there were conflicting theories and research findings on the impacts of

IFR on the economy and share prices and it is crucial to take into account the geographical

locations of the studies. This is in line with the findings of Naik and Padhi (2012, p. 36) and

Heng et al. (2012) which demonstrated a negative and significant relationship between the IFR

and share prices. Fang et al. (2016, pp. 244-245), is the only past study that investigated the

impacts of the IFR on REIT share prices and agreed that the relationship between the two

variables was significant, but inverse. Contrarily, Khan and Zaman (2012) and Barasa (2014)

stated that the relationship was inverse but inconsequential, whereas, Adam and Tweneboah

(2008) and Aroni (2011, p. 309) agreed that it was insignificant but positive.

Zucchi (2017) claimed that the impacts of the IFR on share price movements are dependent on

the geographical location. The historical data evidenced that a rising IFR had more significant

influences on the fluctuations of share prices in emerging countries because the volatility of

stocks is more intense in those regions than in developed ones. The author affirmed that

whether the relationship between the two variables would be positive or negative relies on the

ability to hedge in a certain market and the government’s monetary policy. The outlook of a

rising IFR would lead to fears of a further uprise in the IFR that could trigger the selldown of

stocks. This would, in turn, cause a fall in share prices. Therefore, investors tend to lighten

their investment portfolios when there has been a recent rise in the IFR. Swedroe (2012) also

supported that investors, in general, demand a higher risk premium for stocks in a high IFR or

volatile environment.

According to Andriotis (2011) and REITs and inflation protection (2017), REITs have been

historically perceived as an inflation hedge because real estate rents and values rise when the


IFR rises. This allows REITs to achieve dividend growth and offer a consistent stream of

income to shareholders even under inflationary pressures. Nevertheless, Lu and So (2001, p.

103), Andriotis (2011) and Mowell (2013) agreed that whether a REIT can hedge against

inflation relies on the causes of inflation. The authors stated that a rising IFR can be triggered

by a myriad of causes and only positive ones, such as economic growth provide REITs with

protection. REITs may still be affected by inflationary pressures depending on the markets they

operate in and the central bank policy. Therefore, it is crucial to investigate the relationship

between the IFR in Malaysia and M-REIT share prices.

(f) Interest Rate (IR)

Also, past research findings have mostly claimed that the interest rate (IR) has a significant but

negative relationship with share price movements. However, there are conflicting theories on

the impacts of the IR on share prices. Kaur (2017) stated that a rising IR climate is typically

perceived to lead to falling share prices. According to Harper (2017), REITs are high-yield

investment vehicles because 90 per cent of their taxable profit has to be distributed, in the form

of dividends, to their investors. Thus, REITs are also typically expected to be sensitive to IR

fluctuations. Nevertheless, Simply Safe Dividends (2017) reasoned that a rising IR suggests

opportunities to some investors because it signifies the investors’ expectations for stronger

future economic growth, which could positively drive share price movements. Thus, the

relationship between the IR and share prices relies profoundly on an investor’s risk appetite

(Simply Safe Dividends 2017).

Furthermore, Lloudis (2016) and Nick (2016) supported that fluctuations of the IR have major

impacts on corporate earnings growth, investor risk appetite and stock valuations, which in turn

will impact share price movements significantly. However, the reasons behind the IR

fluctuation will determine the degree and direction of the share price movements. According

to the authors, different countries, or segments, of the global market will have varying

responses to IR fluctuations. Therefore, despite the outcomes of past studies concerning the

relationship between the IR and share prices, it is still crucial to investigate how changes in

Malaysia’s IR will affect the share price movements of M-REITs.


(g) Shariah-Compliance as a Firm-Specific Factor

Conceptually, Shariah-compliance of a REIT is expected to strengthen its performance and

share price movements because being aligned with Sharia law means it is built on tangible real

assets (Islamic Markets 2018). This increases the perception that it is a better investment option

because tangible real assets generally offer greater stability (Aquila Capital 2014; Watt 2015).

Also, it appeals to investors, in general, (other than Muslims) who are prone to ethical decision

making instead of only being profit-oriented (Mohamed & Lusyana 2017, p. 21). According to

Ahmad Tajjudin Rozman et al. (2015, pp. 8-9) and Nordin (2018), flexibility and

diversification are among the advantages of investing in Shariah-compliant REITs and the

rationale behind the positive and significant relationship between Shariah-compliance and

share price movements.

However, Rosly (2018) stated that varying results had been proclaimed by various researchers

concerning the impacts of Shariah-compliance on a firm’s share price and performance.

Miniaoui, Sayani and Chaibi (2015, p. 357) claimed that there had been a widely, and maybe

misleading conception proliferated that Shariah-compliance lowered the risk borne by a firm.

Despite the challenges faced by global REIT markets to introduce and spread Shariah-

compliant REITs in the face of an inadequate and distinct regulatory framework, and standards

that can facilitate the governance of their operations, the M-REIT market is believed to have

great potential to grow in terms of its Shariah-compliant REITs (Malaysia International Islamic

Financial Center (MIFC) 2013; Nordin 2018). This is because the M-REIT market offers clear-

cut guidelines to aid the development of Shariah-compliant REITs (Islamic Markets 2018).

According to Ting and Noor (2007) and Ahmad Tajjudin Rozman et al. (2015, pp. 8-9), the M-

REIT market could play a vital role in increasing the competence of Islamic financial

instruments in Malaysia. Therefore, it is crucial to investigate the relationship between Shariah-

compliance and share price movements in the context of Malaysia, to increase investors’

confidence in investing in Shariah-compliant M-REITs.

The table below illustrates the variables that were put through the different stages of selection

until the subset of candidate predictors to focus on was selected.


Table 4: Variable Selection Process and Outcome

Variable Selection Process and Outcome

Stage 1 Stage 2 Stage 3

Identification of Variables

Analysed in Past Studies


Significance of Variables

Analysed


Added-Value to the

Analysis

1. Market Capitalisation

2. Net Asset Value (NAV)

3. Dividend Yield (DY)

4. Dividend Payout Ratio

(DPR)

5. Dividends per Share

(DPS)

6. Debt to Asset Ratio (D/A

Ratio)

7. Debt to Equity Ratio

(D/E Ratio)

8. Net Income (NI)

9. Earnings per Share (EPS)

10. Price-Earnings Ratio

(P/E Ratio)

11. Retained Earnings (RE)

12. Return on Equity (ROE)

13. Return on Assets (ROA)

14. Size (represented by the

logarithms of total assets)

15. Economic Value Added

(EVA)

16. Debt to Capital ratio

17. First Lag of Share Price


2. Net Asset Value

(NAV)


4. Dividends per Share

(DPS)

5. Debt to Asset Ratio

(D/A Ratio)

6. Debt to Equity Ratio

(D/E Ratio)

7. Net Income (NI)

8. Earnings per Share

(EPS)


(P/E Ratio)

10. Return on Equity

(ROE)

11. Return on Assets

(ROA)

12. Economic Value

Added (EVA),

13. Debt to Capital ratio

14. First Lag of Share

Price

15. Interest Rate (IR)




(P/E Ratio)


5. Inflation Rate (IFR)

6. Shariah-Compliance



19. Exchange Rate (ER)


21. Money Supply

22. Crude Oil Price

23. Gross Domestic Products

(GDP)



17. Money Supply


To sum up, through phase one of this study, which was the identification of factors through a

literature review and synthesis, Market Capitalisation (MC), Dividend Yield (DY), the Price-

Earnings Ratio (P/E ratio) were included in the regression model as the firm-specific factors

that were believed to be driving M-REIT share prices. Shariah-compliance was also later added

as a firm-specific factor in the model to compare its impacts on REIT share prices. On the

contrary, the Interest Rate (IR) and the Inflation Rate (IFR) were included in the regression

model as the macroeconomic independent variables that were believed to be driving M-REIT

share prices. Their relationships with the share price movements of REITs listed on Bursa

Malaysia were analysed and studied.

4.4 Phase Two: Findings of Regression Analysis

For this research, the firm-specific and macroeconomic independent variables were placed in

two separate regression models. The first regression model investigated the impacts of market

capitalisation (MC), dividend yield (DY) and the price-earnings ratio (P/E ratio) on the share

price movements of M-REITs while the second regression model investigated the impacts of

the interest rate (IR) and the inflation rate (IFR) on M-REIT share prices. Shariah-compliance

was included as a firm-specific factor in the third regression model and the differences between

the results were studied and compared.

The results from the first regression model are shown in Table 5.


Table 5: Regression Output of the Firm-specific Independent Variables

Dependent Variable: SP Method: Panel Least Squares Date: 06/10/18 Time: 23:20 Sample: 1/02/2008 12/29/2017 Periods included: 2459 Cross-sections included: 17 Total panel (unbalanced) observations: 35065

Variable Coefficient Std. Error t-Statistic Prob.

C 2.791337 0.024284 114.9467 0.0000 MC 8.87E-08 1.85E-09 47.95447 0.0000 DY -78.23459 1.221155 -64.06606 0.0000 PE 0.001445 0.000174 8.295026 0.0000

R-squared 0.194619 Mean dependent var 1.401511 Adjusted R-squared 0.194550 S.D. dependent var 1.082334 S.E. of regression 0.971361 Akaike info criterion 2.779877 Sum squared resid 33081.54 Schwarz criterion 2.780843 Log likelihood -48734.20 Hannan-Quinn criter. 2.780185 F-statistic 2824.135 Durbin-Watson stat 0.056508 Prob(F-statistic) 0.000000

Table 5 reports the regression estimates for the firm-specific independent variables analysed in

this study. The coefficient estimates indicate that the MC, DY and the P/E ratio have

statistically significant impacts on the share price movements of M-REITs. The null hypothesis

in hypothesis testing states that there is a lack of difference between the experimental groups

being studied, signifying that the predictor variables do not affect the dependent variable. In

the case of examining the impacts of the MC, DY and the P/E ratio and the share prices of M-

REITs, the null hypothesis is rejected and test statistics of 47.95, -64.07 and 8.30 are reported

respectively, corresponding with a zero p-value. Furthermore, the standard error column

reveals the standard errors of the coefficient estimates, through which the statistical reliability

or the variability of the estimates is calculated. The higher the score of the standard errors, the

more statistical noise, or unexplained variability the coefficient estimate has.

The first regression model aims to test the alternative hypotheses formulated on the

relationships between the MC, DY and the P/E ratio and the M-REIT share prices, as shown

below (refer to Para 3.5 Hypotheses).


Table 6: Hypotheses (H1, H2 and H3)

Hypothesis Result

H1 There is a positive relationship between the market capitalisation

(MC) of an M-REIT and its share price.

Supported

H2 There is a positive relationship between the dividend yield (DY) of

an M-REIT and its share price.

Rejected

H3 There is no positive relationship between the price-earnings ratio

(P/E ratio) of an M-REIT and its share price.

Rejected

H1 is supported because the regression estimates in Table 5 show a positive relationship

between the MC and M-REIT share prices. It indicates that with the increase of an M-REIT’s

MC, its share price would rise as well, and vice-versa, holding other independent variables

unchanged. H2, however, is rejected because the coefficient estimates in Table 5 reveal a

negative relationship between the DY and M-REIT share prices. This indicates that an increase

in the DY of an M-REIT would lead to a fall in its share price, and vice-versa, while other

independent variables are held constant. H3 stated that there is no positive relationship between

an M-REIT’s price-earnings ratio (P/E ratio) and its share price. This is inconsistent with the

coefficient estimates in Table 5 which report a positive relationship between the two variables,

hence, H3 is rejected as well. The coefficient estimates indicate that the share price of an M-

REIT would rise following a rise in the P/E ratio, and vice-versa.

Besides, the adoption of a fixed-effect or random-effect model for the regression model was

determined through the Hausman test.


Table 7: Results of the Hausman Test Run of the Regression Model of Firm-specific

Independent Variables

Correlated Random Effects - Hausman Test Equation: RANDOM Test cross-section random effects

Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob. Cross-section random 33.266462 3 0.0000

Cross-section random effects test comparisons:

Variable Fixed Random Var(Diff.) Prob. MC 0.000000 0.000000 0.000000 0.0000

DY -27.269269 -27.273597 0.000001 0.0003 PE -0.000495 -0.000495 0.000000 0.1339

Cross-section random effects test equation: Dependent Variable: SP Method: Panel Least Squares Date: 06/10/18 Time: 23:25 Sample: 1/02/2008 12/29/2017 Periods included: 2459 Cross-sections included: 17 Total panel (unbalanced) observations: 35065

Variable Coefficient Std. Error t-Statistic Prob. C 1.918407 0.005556 345.2950 0.0000

MC 3.43E-09 3.91E-10 8.776799 0.0000 DY -27.26927 0.285570 -95.49072 0.0000 PE -0.000495 3.71E-05 -13.35566 0.0000

Effects Specification Cross-section fixed (dummy variables) R-squared 0.968616 Mean dependent var 1.401511

Adjusted R-squared 0.968599 S.D. dependent var 1.082334 S.E. of regression 0.191794 Akaike info criterion -0.464222 Sum squared resid 1289.125 Schwarz criterion -0.459394 Log likelihood 8158.975 Hannan-Quinn criter. -0.462684 F-statistic 56926.33 Durbin-Watson stat 0.016601 Prob(F-statistic) 0.000000


Table 7 shows the results of the Hausman test that was carried out through EViews to determine

if the model is suitable to be a fixed-effect model or a random-effect model. The null hypothesis

states that the random-effect model is appropriate for the regression model, while the

alternative hypothesis, the fixed-effect model is appropriate. As shown in the table, the p-value

of the test summary is less than 5% which indicates that the null hypothesis should be rejected

while the alternative hypothesis should be accepted. Therefore, the fixed-effect model is

appropriate to identify the relationships between the predictor variables, MC, DY and the P/E

ratio, and the M-REIT share prices. The result matches the assumption made in Para 3.8 Data

Analysis that a fixed-effect model should be adopted. The assumptions of the fixed-effect

model include that it is necessary to control the individual characteristics that may cause bias

to the independent variables (the relationship between the M-REIT’s error term and the

independent variables). The impacts of the time-invariant characteristics are eliminated

through the fixed-effect model so that the net effect of the independent variables could be

evaluated. The rationale behind the Hausman Test also includes the time-invariant

characteristics that are distinctive to the respective entity. Hence, there should not be any

relationship between the constant or error term that apprehended the individual characteristics

of an entity and other entities’ error terms.

Moreover, the results from the second regression model are shown in Table 8.


Table 8: Regression Output of the Macroeconomic Independent Variables

Dependent Variable: SHARE_PRICE__RM_ Method: Panel EGLS (Cross-section random effects) Date: 03/29/18 Time: 17:44 Sample: 1/02/2008 12/29/2017 Periods included: 2459 Cross-sections included: 17 Total panel (unbalanced) observations: 35065 Swamy and Arora estimator of component variances


C 1.000930 0.218067 4.590005 0.0000 INTEREST_RATE____ 80.32106 1.310364 61.29673 0.0000 INFLATION_RATE____ -12.84149 0.287543 -44.65936 0.0000

Effects Specification S.D. Rho

Cross-section random 0.898192 0.9508 Idiosyncratic random 0.204365 0.0492

Weighted Statistics

R-squared 0.101542 Mean dependent var 0.007301 Adjusted R-squared 0.101491 S.D. dependent var 0.215693 S.E. of regression 0.204436 Sum squared resid 1465.389 F-statistic 1981.318 Durbin-Watson stat 0.013772 Prob(F-statistic) 0.000000

Unweighted Statistics

R-squared -0.009046 Mean dependent var 1.401511 Sum squared resid 41447.19 Durbin-Watson stat 0.000487

Table 8 shows the results of the second regression model which investigated the association

between the macroeconomic predictor variables studied in this research, the IR and the IFR

with M-REIT share prices. The regression estimates in Table 8 reveal that both the IR and the

IFR have a significant relationship with the share price movements of M-REITs. The null

hypothesis states that there is a lack of difference between the experimental groups being

studied, indicating that the predictor variables do not affect the dependent variable. The null


hypothesis is rejected because the result showed a zero p-value for both the IR and the IFR,

corresponding with test statistics of 61.30 and -44.66 respectively.

The second regression model aims to test the alternative hypotheses formulated on the

relationships between the IR, IFR and M-REIT share prices as shown below (refer to Para 3.5

Hypotheses).

Table 9: Hypotheses (H4 and H5)

Hypothesis Result

H4 There is no positive relationship between the interest rate (IR) and


Rejected

H5 There is no positive relationship between the inflation rate (IFR) and


Supported

H4 is rejected because the coefficient estimates in Table 8 reveal a positive relationship between

the IR and M-REIT share prices. It provides an indication that a rise of IR would lead to upward

share price movements of the M-REITs, and vice-versa, holding other independent variables

constant.

On the other hand, H5 is accepted because the coefficient estimates in Table 8 show a negative

relationship between the IFR and M-REIT share prices. The result shows that a rising IFR

would cause a decline in M-REIT share prices, and vice-versa.

The Hausman test was also run to examine if a fixed-effect or random-effect model should be

adopted for the regression model.



Macroeconomic Independent Variables

Correlated Random Effects - Hausman Test Equation: Untitled Test cross-section random effects

Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.

Cross-section random 10.385338 2 0.0056


Variable Fixed Random Var(Diff.) Prob.

INTEREST_RATE____ 80.317249 80.321057 0.000002 0.0032 INFLATION_RATE____ -12.841187 -12.841490 0.000000 0.0389

Cross-section random effects test equation: Dependent Variable: SHARE_PRICE__RM_ Method: Panel Least Squares Date: 03/29/18 Time: 17:44 Sample: 1/02/2008 12/29/2017 Periods included: 2459 Cross-sections included: 17 Total panel (unbalanced) observations: 35065


C 0.838432 0.009810 85.46607 0.0000 INTEREST_RATE____ 80.31725 1.310365 61.29380 0.0000 INFLATION_RATE____ -12.84119 0.287543 -44.65830 0.0000

Effects Specification

Cross-section fixed (dummy variables)

R-squared 0.964366 Mean dependent var 1.401511 Adjusted R-squared 0.964347 S.D. dependent var 1.082334 S.E. of regression 0.204365 Akaike info criterion -0.337277 Sum squared resid 1463.697 Schwarz criterion -0.332690 Log likelihood 5932.309 Hannan-Quinn criter. -0.335816 F-statistic 52691.50 Durbin-Watson stat 0.013788 Prob(F-statistic) 0.000000


Table 10 reveals the results of the Hausman test conducted through EViews to evaluate if the

regression model is fit to be a fixed-effect model or a random-effect model. The null hypothesis

states that the random-effect model is appropriate, while the alternative hypothesis, the fixed-

effect model is appropriate. As shown in Table 10, the p-value is less than 5% which implies

that the null hypothesis should be rejected, while the alternative hypothesis should be accepted.

Thus, a fixed-effect model is appropriate to determine the relationship between the independent

variables, IR and IFR and M-REIT share prices. This matches with the assumption made in

Para 3.8 Data Analysis.

Other than the two regression models above, Shariah-compliance was added subsequently as a

firm-specific factor in the regression model that analyses the relationships between the selected

firm-specific regressors and M-REIT share prices. The results are shown in Table 11.

Table 11: Regression Output of the Firm-specific Independent Variables (including

Shariah-Compliance)

Dependent Variable: SP Method: Panel Least Squares Date: 06/10/18 Time: 22:40 Sample: 1/02/2008 12/29/2017 Periods included: 2459 Cross-sections included: 17 Total panel (unbalanced) observations: 35065


C 2.241996 0.024175 92.74133 0.0000 MC 8.38E-08 1.74E-09 48.21278 0.0000 DY -57.56392 1.185870 -48.54152 0.0000 PE 0.001423 0.000164 8.700928 0.0000

SHARIAH_COMPLIANT 0.899153 0.013126 68.50143 0.0000

R-squared 0.289687 Mean dependent var 1.401511 Adjusted R-squared 0.289606 S.D. dependent var 1.082334 S.E. of regression 0.912244 Akaike info criterion 2.654324 Sum squared resid 29176.54 Schwarz criterion 2.655531 Log likelihood -46531.93 Hannan-Quinn criter. 2.654708 F-statistic 3574.632 Durbin-Watson stat 0.057196 Prob(F-statistic) 0.000000


The coefficient estimates shown in Table 11 provide sufficient statistical proof to conclude that

the relationships between the MC, DY, the P/E ratio and the Shariah-compliance dummy and

M-REIT share prices respectively are significant. Other than the original firm-specific

independent variables included in the first regression model, the hypothesis concerning the

relationship between Shariah-compliance and the share price movements of M-REITs is also

examined in Table 11.

Table 12: Hypotheses (H1, H2, H3 and H6)

Hypothesis Result

H1 There is a positive relationship between the market capitalisation

(MC) of an M-REIT and its share price.

Supported

H2 There is a positive relationship between the dividend yield (DY) of

an M-REIT and its share price.

Rejected

H3 There is no positive relationship between the price-earnings ratio

(P/E ratio) of an M-REIT and its share price.

Rejected

H6 There is a positive relationship between Shariah-compliance, as a

firm-specific factor, and M-REIT share prices.

Supported

Despite the insertion of Shariah-compliance as one of the firm-specific independent variables,

the significance and relationships of the MC, DY and the P/E ratio and M-REIT share prices

are found to be similar to the output of the first regression model (refer to Table 5), H1 is

accepted while H2 and H3 are rejected. As shown in the regression output in Table 11, the MC

and the P/E ratio respectively have a positive relationship with the M-REIT share prices while

the DY is negatively related to the share prices.

The findings also reveal that an increase of the MC would cause the M-REIT share prices to

rise, and vice-versa, holding other independent variables unchanged. However, the magnitude

of the impact is reduced, as compared to the coefficient estimates indicated by the outputs in


the first regression model (refer to Table 5). Furthermore, the findings in Table 11 also indicate

that an upswing of an M-REIT’s DY would lead to a decline in its share price, and vice-versa,

holding other independent variables constant. The impact is also significantly weakened, as

compared to the coefficient estimates shown in the results of the first regression model.

Contrarily, the outputs concerning the impact of the P/E ratio on the share prices were similar

in both the first and third regression models.

Also, the analysis reveals a significant and positive relationship between Shariah-compliance

and the share prices of M-REITs. Therefore, H6 is accepted (refer to Para 3.5 Hypotheses). The

significant positive relationship between the Shariah-compliance dummy and M-REIT share

prices suggests that in general, the shares of Shariah-compliant REITs can be traded at a higher

price than those of conventional REITs. This is in line with the widely held perception that

Shariah-compliant REITs (especially, in Malaysia as it is the pioneer of Shariah-compliant

REITs) have significant and favourable impacts on the performance, returns and share price

movements of REITs (Malaysia International Islamic Financial Center (MIFC) 2013).

The Hausman test, as shown in Table 13, was run via EViews to examine if the fixed-effect or

random-effect model is fit for the regression model.


Table 13: Results of the Hausman Test Run of the Regression Model of the Firm-Specific

Independent Variables (including Shariah-Compliance)

Correlated Random Effects - Hausman Test Equation: RANDOM Test cross-section random effects

Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.

Cross-section random 48.059142 4 0.0000


Variable Fixed Random Var(Diff.) Prob.

MC 0.000000 0.000000 0.000000 0.0000 DY -26.788154 -26.777252 0.000021 0.0177 PE -0.000490 -0.000490 0.000000 0.0032

SHARIAH_COMPLIANT 0.052512 0.054270 0.000000 0.0010

Cross-section random effects test equation: Dependent Variable: SP Method: Panel Least Squares Date: 06/10/18 Time: 23:09 Sample: 1/02/2008 12/29/2017 Periods included: 2459 Cross-sections included: 17 Total panel (unbalanced) observations: 35065


C 1.899735 0.007668 247.7492 0.0000 MC 3.41E-09 3.91E-10 8.742145 0.0000 DY -26.78815 0.316344 -84.68034 0.0000 PE -0.000490 3.71E-05 -13.21843 0.0000

SHARIAH_COMPLIANT 0.052512 0.014866 3.532415 0.0004 Effects Specification

Cross-section fixed (dummy variables)

R-squared 0.968627 Mean dependent var 1.401511 Adjusted R-squared 0.968609 S.D. dependent var 1.082334 S.E. of regression 0.191762 Akaike info criterion -0.464521 Sum squared resid 1288.666 Schwarz criterion -0.459452 Log likelihood 8165.216 Hannan-Quinn criter. -0.462906 F-statistic 54098.35 Durbin-Watson stat 0.016567 Prob(F-statistic) 0.000000


The p-value of the test summary is below 0.05 or 5%, indicating that the null hypothesis should

be rejected and, hence, the fixed-effect model should be adopted to identify the relationships

between the independent variables, MC, DY, the P/E ratio and the Shariah-compliance (dummy

variable), and the M-REIT share prices (dependent variable). The result is in line with the

assumption stated in Para 3.8 Data Analysis that a fixed-effect model would be fit for the

analysis.

4.5 Summary

This chapter has discussed in depth the findings or identification of the factors affecting M-

REIT share prices through a literature review and synthesis process, as well as the selection

criteria for potential predictor variables. Moreover, the findings of the regression analysis

showed that all of the six predictor variables selected for this study were significantly related

to M-REIT share prices. The relationships between M-REIT share prices and market

capitalisation (MC), the P/E ratio, the IR and the Shariah-compliance (dummy) are positive,

whereas, the DY and IFR respectively have a negative relationship with M-REIT share prices.

The rationale behind the relationship of each independent variable and M-REIT share prices

found through the analyses is discussed in the next chapter.


CHAPTER FIVE DISCUSSIONS

5.1 Introduction

This chapter discusses the possible reasons behind the summary of the analysis results, as

shown in Table 5, Table 8 and Table 11 (refer to Para 4.4 Phase Two: Findings of Regression

Analysis). The discussions include both the empirical and theoretical justifications of such

findings.

5.2 Positive Relationship between Market Capitalisation (MC) and M-REIT Share Prices

The regression output reported in Table 5 (refer to Para 4.4 Phase Two: Findings of Regression

Analysis) shows that the market capitalisation (MC) of an M-REIT has a significant and

positive relationship with its share price. This matches with Hypothesis 1 (H1) drafted in Para

3.5 Hypotheses. Despite the differences of this research with past studies in terms of the

research country, population, sample period, research methodology and the like, the result is

consistent with many of the past studies 1 such as Mohammad and Zolkifli (2013) and Olanrele

(2014, p. 500) which investigated the relationship between a REIT’s MC and its share price

movements. Past studies 2, such as Avdalovic (2018, p. 19) also agreed that larger entities, in

general, offered both the benefit of higher returns and lower risk. Only Strange and Tang (2000)

disagreed and stated that MC had a significant but negative relationship with share price

movements.

In its simplest explanation, MC represents an entity’s phase in its operations and development.

Investments in large-cap stocks are usually considered as being sturdier which equates with

stronger security for investors than investments in mid-cap and small-cap entities. Typically,

1 Ziering, Liang and McIntosh (1999, p. 65), Conover, Friday and Howton (2000, p. 162), Below,

Stansell and Coffin (2000, p. 277), Clayton and MacKinnon (2000) and Ali (2006)

2 Allahawiah and Amro (2012, p. 239), Sharif, Purohit and Pillai (2015, p. 207) and Aveh and Vitor

(2017)


investors arrive at decision making after they have evaluated the risk and return trade-off of an

investment. Large-cap entities give rise to lower risk but more conservative growth potential.

On the contrary, mid-cap entities are entities in the phase of expanding their market share and

strengthening their business competence. This is an important phase that shapes the future of

an entity and determines if the entity would rise up to its fullest potential. Thus, mid-cap entities

may provide more growth than entities with a larger MC while offering less stability.

Dissimilarly, small-cap entities are typically perceived as having limited access to resources.

This is the reason why they could be more sensitive and vulnerable to changes in the business

climate and particularly the domestic economy. They could be more defenceless against intense

competition and the unpredictability of fledgeling markets. Investors who buy the shares of

small-cap entities are usually risk seekers who are willing to endure the short-run volatility of

share price fluctuations for the potential of significant returns and growth. In the general market

and investors’ perspectives, MC has much to say about an entity’s stage of development and

its potential returns in the future. Therefore, it has significant impacts on the decision of

investors whether to invest in an entity’s shares, hence, affecting the share price movements

significantly.

Aseambankers Malaysian Berhad (2007), Rubel (2015) and Frankel (2016) stated that one of

the most prominent assessments that can be conducted on real estate investors is their level of

risk tolerance. The authors agreed that the high return and low-risk nature of a REIT make it

an attractive investment instrument for investors who tend to avoid both risk and uncertainty.

Thus, as further backed by Ung (2012) and Rao (2019), REIT investors are typically more

disinclined to take on risk and uncertainty. It is also vital to understand that growth is not a

definite sacrifice for risk-avoiding investors, even in the M-REIT environment. There is still

potential for rising income and share price growth. According to Frankel (2016), while REITs

are suitable investment instruments for risk-avoiding investors, it is not risk-free. It simply

means that REITs give more cautious investors a higher sense of security. When an M-REIT’s

MC becomes larger, it implies that its access to resources and capital markets has been extended,

making the implementation of economies of scale and diversification of the portfolio more

attainable. This leads to a more resilient cushioning against fluctuations in the business climate.

It is also an indication that the M-REIT has become more equipped to cope with abrupt falls in

demand or unexpected events, especially, during an economic contraction. With an increasing

MC, the stability of the M-REIT is seen to be strengthened. This makes its actual returns easier


to predict and, hence, a potentially less risky investment. As the investors in M-REITs are

typically risk-avoiding, they react to rising MC positively because a larger MC signifies less

volatility and lower risk with stable but conservative growth. The demand for shares rises along

with the growing MC of M-REITs, thus, the relationship between the MC and share price is

both positive and significant.

5.3 Negative Relationship between Dividend Yield (DY) and M-REIT Share Prices

The result reported in Table 5 shows that the dividend yield (DY) of an M-REIT has a

significantly negative relationship with its share price movements. This is inconsistent with

Hypothesis 2 (H2) drafted in the initial stage of this research that there is a positive relationship

between an M-REIT’s DY and its share price (refer to Para 3.5 Hypotheses).

The result is consistent with the findings of some past studies, namely; Malhotra, Chandiwala

and Tandon (2013, p. 94), Sharif, Purohit and Pillai (2015, p. 213) and Aveh and Vitor (2017)

who claimed that the two variables were significantly and negatively related. On the contrary,

Strange and Tang (2000), Khan (2009), Mohammad and Zolkifli (2013) and Chiang (2014)’s

findings reported a significant and positive relationship between an entity’s DY and its share

price. Strange and Tang (2000) reasoned that a higher DY is a representation that an entity is

more committed to distributing profits to its shareholders and, hence, leading to investors’

perception of stronger future earnings capabilities. Contrarily, Khan (2009), Mohammad and

Zolkifli (2013) and Chiang (2014) did not explain the possible reasons behind their findings.

Conceptually, according to Scottrade (2014) and Grant (2018), the DY is often assumed to be

positively related to the movements of share prices because an entity that distributes higher

dividend payments is typically perceived to be having brighter prospects. However, Scottrade

(2014) stated that it is crucial to understand that it is only when the dividend issued is higher

than expected that the market sentiment would shift and that the share price would rise. This is

also supported by Grant (2018) who asserted that although the DY or a dividend payment

represents the likelihood of generating recurring investment return, it is the perceived prospects

implied by such information that motivates the investors to buy or retain the entity’s shares.


Malhotra, Chandiwala and Tandon (2013, p. 94), Sharif, Purohit and Pillai (2015, p. 213) and

Aveh and Vitor (2017) found that the DY was negatively related to share price movements,

which is consistent with the test summary of the regression output in Table 5, but the results

remained unexplained. In theory, according to Thomsett (2018), it is also possible for dividend

payments or the DY to have a negative relationship with an entity’s share price, especially, for

mutual funds which function similarly to REITs. They asserted that the share price of such an

entity will experience a fall, followed by a higher dividend pay-out because a dividend

increases the entity’s value and when it has been distributed to the shareholders, the entity’s

value decreases. Therefore, it may lead to the depreciation of the market value of the shares.

It is imperative to look at the potential causes of the negative relationship between the DY and

the share price in the context of M-REITs. REITs are basically renowned for their high yield

characteristics. According to Leigh (2017), the tax treatment of M-REITs largely relies on the

percentage of taxable income that they distribute to shareholders in the form of dividends. M-

REITs are subject to a 24 per cent rate of corporate income tax if they do not distribute 90 per

cent, or more, of their taxable income to shareholders (Leigh 2017). Therefore, in Malaysia,

the dividend pay-out of a REIT to its shareholders is usually as high as 90 per cent, or more, of

its taxable income for the accounting period. This is backed by the financial highlights outlined

in the annual reports of the 17 M-REITs studied, that from the year 2008 to 2017, most of them

did not incur any tax expenses. This indicates that M-REITs utilised the beneficial tax treatment

by distributing 90 per cent, or more, of their taxable income to shareholders. It also evidences

the stability of the dividend policies of M-REITs. These characteristics are attractive to

investors, especially, for risk and uncertainty avoiding investors. When both the income

streams and dividend pay-outs are relatively stable, investors tend to have more confidence in

an entity’s dividend payments. Therefore, according to Abdullah (2014, p. 16), it may not be a

positive relationship between the dividend payments or the DY and the share prices of entities,

such as REITs. The relationship with and the impacts of the DY on share prices rely largely on

investors’ confidence in M-REITs’ dividend policies.

Besides, the DY measures the amount of dividends that shareholders receive in proportion to

the share price. Even though a lower DY may indicate that a REIT is in distress and, therefore,

had to cut down on its dividend payments, it may also be a sign of a rising share price. On the

contrary, a higher DY may be a sign of a depressed share price. In the case of M-REITs, due


to the stability of their dividend policies and pay-outs, investors have confidence in the REITs’

future and are not unduly worried about the dividend distribution. Therefore, when an M-

REIT’s DY falls, it may not indicate bad news but may just be caused by a rising share price,

hence, the investors may react positively to it.

5.4 Positive Relationship between Price-Earnings Ratio (P/E Ratio) and M-REIT Share

Prices

The regression output in Table 5 reported a significant and positive relationship between an M-

REIT’s P/E ratio and its share price. The result is inconsistent with Hypothesis Three (H3)

(refer to Para 3.5 Hypotheses). However, the result is in line with past studies, namely;

Malhotra, Chandiwala and Tandon (2013, p. 94), Geetha and Swaaminathan (2015, p. 109) and

Sharif, Purohit and Pillai (2015, p. 213) which analysed the relationship between the two

variables. The findings were unexplained by the authors, except for Malhotra, Chandiwala and

Tandon (2013, p. 94) who asserted that investment decisions were affected by the actual value

of an entity and its earnings which were perceived as a representation of the possible returns

of the investment. Contrarily, Khan (2009) and Singh (2018)’s analysis asserted that the P/E

ratio had no significant impact on share price movements but made no explanation on such

outcomes.

Murphy (2018) claimed that investors have higher expectations of the earnings growth

prospects from entities with a higher P/E ratio than those with a lower P/E ratio. Therefore, the

share price of an entity which has a high P/E ratio tends to be overvalued. Conceptually, this is

an indication that investors who invest in the shares of an entity which has a higher P/E ratio

carry a higher risk of losing their investments if their expectations of the higher earnings growth

are not eventually met. On the other hand, a lower P/E ratio may denote an undervalued share

price, which is likely to rise soon. This is backed by Jain (2016) and The Motley Fool (2017)

which affirmed that shares with a low P/E ratio are recognised as having lower market prices,

thus, are anticipated to yield more lucrative return in the subsequent period. Therefore, an entity

with a lower P/E ratio may attract more investors to invest in its shares. However, why is this

not the case in the REIT market of Malaysia? The findings of this research concluded a positive

and significant relationship between the P/E ratio and share prices of M-REITs. The possible

reasoning behind such a result is that the complexity of what a higher or lower P/E ratio


represents is not taken into account by, or is not well known, among the investors of M-REITs.

Rather, they regard market expectations of a higher or lower P/E ratio to be reliable, instead of

being the sign of an overvalued or undervalued share price. This is supported by Thean (2017)

who claimed that investors of M-REITs believed that market expectations were realisable and,

thus, despite the gloomy international economic outlook, they still perceived Malaysia as a hub

for investments. Therefore, a higher P/E ratio may mean higher expectations of earnings growth

for investors, in general, and thus, attracting more investments in M-REITs. This provides the

rationale behind a significant and positive relationship between the P/E ratio of an M-REIT

and its share price.

5.5 Positive Relationship between Interest Rate (IR) and M-REIT Share Prices

The regression output shown in Table 8 (refer to Para 4.4 Phase Two: Findings of Regression

Analysis) reveals a significant and positive relationship between the interest rate (IR) and the

share prices of M-REITs. This does not match with Hypothesis 4 (H4) (refer to Para 3.5

Hypotheses). The finding is not in line with most past research 1 which investigated the

relationship between two variables. All of the past studies consistently concluded that the IR

would impact share prices inversely and significantly except for Wong (2015) and Diedrich

(2017). According to the authors, the IR’s impacts on REIT share prices were insignificant.

Nevertheless, this is highly refutable in theory, because REITs are known to be IR sensitive.

Not only did the empirical studies evidence a negative relationship between the two variables,

in theory, but a rising IR climate is also typically perceived to have negative impacts on share

price movements (Zambell 2018). This is because an increasing IR denotes a decline in the

present value of an entity’s future cash flows. According to Harper (2017), REITs are high-

yield investment vehicles, because 90 per cent of their taxable profit has to be distributed in

the form of dividends to its investors. This is the reason why they are also known as being IR

sensitive. However, Lloudis (2016), Nick (2016) and Simply Safe Dividends (2017) reasoned

that a rising IR may be perceived as an opportunity to some investors because it signifies

investors’ expectation for stronger future economic growth, which could lead to an upward

1 Adam and Tweneboah (2008), Aroni (2011, p. 310) and Heng et al. (2012), Cheong et al. (2006), Hooi and Smyth (2011), Ito (2013) and Fang et al. (2016, p. 245)


shift of the share prices. Hence, the relationship between IR and the share price relies

profoundly on the industry and the environment that is being observed. Also, Lloudis (2016)

asserted that although REITs are known for their IR sensitive characteristic, the causes of the

IR’s rising or falling are vital. Therefore, the fluctuations of a country’s IR may not necessarily

have a significant impact on or a negative relationship with the REITs’ share prices.

On the surface, it is illogical to anticipate a positive relationship between the IR and the share

prices of M-REITs. Other than the discussion above, this is also because REITs are typically

highly-indebted due to purchasing assets, hence, a rising IR would reduce their capability to

service their debts. Nevertheless, as stated, the reasons behind a rising or falling IR are the keys

to deciding whether the relationship with M-REIT share prices would be positive or negative.

According to Karim (2013, p. 1068), Tan (2014) and MIDF Research (2017), the level of the

domestic IR or overnight policy rate (OPR) is relatively more stable in Malaysia than in many

countries. Due to the IR targeting and benchmarking set by the central bank, the Malaysian IR

has only fluctuated between 2 per cent and 3.50 per cent over the years. In Malaysia’s relatively

stable IR climate, a rising IR environment usually indicates a growing economy, thus, the

economy could be in distress when there is a fall in the IR. When the IR rises because of an

advancing economy, it may have positive impacts on REIT share prices because business

expansion is expected, premises can be rented out more easily and consumer spending is

deemed to rise. This could explain why the regression output shown in Table 8 shows a

significant and positive relationship between the IR and the share prices of M-REITs.

5.6 Negative Relationship between Inflation Rate (IFR) and M-REIT Share Prices

The result in Table 8 (refer to Para 4.4 Phase Two: Findings of Regression Analysis) reports a

significant but negative relationship between the inflation rate (IFR) of Malaysia and the share

price movements of M-REITs. This matches with Hypothesis 5 (H5) (refer to Para 3.5

Hypotheses). The finding is also consistent with some of the past research 1 like Naik and Padhi

(2012, p. 36) which affirmed that the relationship between the IFR and share prices was

significantly negative. However, other past studies, namely; Adam and Tweneboah (2008),

Aroni (2011, p. 309), Khan and Zaman (2012) and Barasa (2014) found that the relationship

1 Heng et al. (2012), Fang et al. (2016, pp. 244-245), Hussein (2017) and Singh (2018)


between the two variables was insignificant. The possible reasons behind those results

remained unexplained.

In theory, the IFR should have no significant effect on share prices as entities can simply

transfer the burden of rising costs to consumers by increasing prices. Nevertheless, this often

may not happen in reality. In the global competitive environment, an entity may lose its

competitiveness when the prices of its products or services increase. Thus, often the burden of

increasing costs has to be largely borne by the entity itself, for fear of losing its customers. This

signifies that IFR tends to impact an entity’s profits and earnings inversely which is usually

reflected in its share price. Besides, the IFR is presumed to be negatively related to share prices

because when the IFR rises, the purchasing power of a currency deflates, and vice-versa.

According to Zucchi (2017), the deceleration of an economy is also followed by a rising IFR

until it is stabilised. The author asserted that the relationship between the two variables relies

on the geographical locations of the entities or the industry being observed. Based on the

historical evidence, the share prices of entities established in developing or emerging countries,

like Malaysia, are more significantly affected by IFR fluctuations. This is because the volatility

of shares is more intense in those countries. Whether the relationship would be positive or

negative is also dependent on the entity’s ability to hedge in a certain market. As affirmed by

Ung (2012) and Rao (2019), Malaysian investors, especially, those interested in the M-REIT

industry, are more prone to avoid risk and uncertainty. Thus, a rising IFR climate tends to cause

fears of further elevation in the IFR. This would, in turn, lead to the sell-down of shares, as

investors are inclined to lighten their investment portfolios when there has been a recent rise in

the IFR, causing a downward movement in the M-REIT share prices. Swedroe (2012)

supported that in a high IFR and volatile market, investors typically demand a higher risk

premium of investment. These are the potential causes of the significant, but negative,

relationship between the IFR in Malaysia and the share prices of M-REITs.

5.7 Positive Relationship between Shariah-Compliance and M-REIT Share Prices

In the third regression model, Shariah-compliance was included as a firm-specific independent

variable. A dummy variable was created to indicate if an M-REIT was a conventional M-REIT

or a Shariah-compliant M-REIT. The regression output shown in Table 11 (refer to Para 4.4

Phase Two: Findings of Regression Analysis) shows that Shariah-compliance is positively and


significantly driving the share price movements of M-REITs. This is consistent with

Hypothesis 6 (H6) (refer to Para 3.5 Hypotheses) and the findings of most past studies 1.

However, Reddy and Fu (2014) and Farooq and Alahkam (2016) claimed that the two variables

were negatively and significantly related. Dissimilarly from other past studies, Morad and

Masih (2015) compared the reactions of Shariah-compliant REITs and conventional REITs

against the macroeconomic indicators, IR and IFR, and found that the impacts of Shariah-

compliance on the dependent variables were insignificant.

Other than the empirical evidence, conceptually a Shariah-compliant REIT is perceived to be

a better investment option than conventional ones, especially, in countries like Malaysia where

there are a considerable number of Muslim investors. Shariah-compliant M-REITs appeal not

only to local Muslim investors but also Muslim investors globally because the Shariah-

compliant M-REIT market has been proven to be the most successful, as compared to the ones

in other countries. The first listed Shariah-compliant REIT was introduced by Malaysia and

more clear-cut guidelines of Shariah-compliance were provided by the country’s Securities

Commission (Islamic Markets 2018). This has led to the subsequent success of the growth and

development of the Shariah-compliant M-REIT market. According to the Malaysia

International Islamic Financial Center (MIFC) (2013) and Nordin (2018), the Shariah-

compliant REIT market in Malaysia is still expected to expand.

Also, Shariah-compliant REITs are built on real tangible assets which offer higher stability.

They also offer more flexibility and diversification and these benefits appeal to investors, in

general, as well (Ahmad Tajjudin Rozman et al. 2015, pp. 8-9; Nordin 2018). According to

Mohamed and Lusyana (2017, p. 61), investors, in general, are increasingly opting for ethical

investment decisions rather than being solely profit-oriented. This has led to a more optimistic

outlook for the Islamic markets. Therefore, unsurprisingly the findings of this study report a

significant and positive relationship between Shariah-compliance and M-REIT share prices.

On top of this, the M-REIT market is believed to be playing a vital role in facilitating the

growth and spread of Islamic markets in Malaysia.

1 Mohamad (2015), Foo and Muhammad (2015), Yazi, Morni and Song (2015, p. 1019) and Mohamed and Lusyana (2017, p. 61)


5.8 Summary

In conclusion, Chapter Five has discussed the rationale behind the results of the analyses

conducted for this research.


CHAPTER SIX CONCLUSION, CONTRIBUTIONS, IMPLICATIONS AND RECOMMENDATIONS

6.1 Summary of Thesis

This thesis concentrates on investigating the factors driving the share price movements of

REITs in Malaysia. Chapter One is the introduction to this research thesis and comprises; the

background of the study, an outline of the differences between equity, mortgage and hybrid

REITs and the different types of M-REITs, whether they are conventional or Shariah-compliant,

the problem statement, which explains the motivation of this study, and the importance of

reducing the gap or developing a solution to ease the problem, the research aims and objectives,

research questions and a preview of the structure of the thesis.

Furthermore, Chapter Two mainly contains a literature review of the factors driving share price

movements. At the beginning of the chapter, the history and prospects of the real estate

investment trust (REIT) industries in various countries were reviewed to give an insight into

Malaysian REITs’ (M-REITs) position, as compared to the REITs in other countries which are

more prominent in growth, development and performance. This was followed by a review of

the factors affecting share price movements in general. There are two subsections in this part

of the study. In the first subsection, the past studies which have focused on firm-specific factors

affecting the share prices, in general, were reviewed. As for the second subsection, the past

studies that have concentrated on the impacts of macroeconomic factors on share prices, in

general, were reviewed. Subsequently, a literature review on the past studies that have focused

on the factors that drive the movements of REIT share prices was carried out. The factors

analysed were categorised into a few subsections, namely; the interest rate (IR) and the inflation

rate (IFR), earnings, dividends and net income (NI), financial gearing and leverage, net asset

value (NAV) and market capitalisation (MC). This was followed by the past studies which built

their research on the comparison of conventional and Shariah-compliant organisations or

REITs. Most of the past studies concluded that Shariah-compliance would drive share prices

positively. The literature review underpinned the conceptual framework, hypotheses and the

backbone of this research study.


Chapter Three explores the research methodology adopted in this research thesis. The various

subsections comprise a write up on the research philosophy, the research framework, the

variable selection process, the hypotheses, the conceptual framework and the data collection

and data analysis process. The research philosophy adopted in this study is the post-positivist

research paradigm which is highly associated with quantitative methodology. It is also

deductive research, an empirical study with a close analysis of secondary data. In the research

framework subsection, an explanation of the two phases of the study was provided. The first

phase was the identification of factors through a literature review and synthesis where the past

studies were not only reviewed but critically analysed and synthesised. Therefore, findings and

elements of various past studies were combined to form a new whole, comparing and

concluding the findings gathered. The second phase was the quantitative and non-experimental

analysis where the relationships between independent variables selected and the share prices

of M-REITs were investigated through panel data analysis. Subsequently, an overview of the

variable selection process was provided. This was followed by a subsection which discussed

the conceptual framework which formed the foundation of the study. Market capitalisation

(MC), dividend yield (DY), price-earnings ratio (P/E ratio), interest rate (IR), inflation rate

(IFR) and Shariah-compliance were believed to be impactful on M-REIT share prices. Besides,

the subsection outlining the data collection matters included the details on the secondary data

and the data sources of this study, the sample selection and limitations. The entire population

of M-REITs was intended to be included in the analysis. Nevertheless, information on the KIP

REIT, which was newly established when the analysis was conducted, was either unavailable

or highly limited. Therefore, it was excluded from the dataset. Panel data analysis was adopted

and the dataset was of an unbalanced nature. In the data analysis subsection, the additional

disturbance of the unbalanced panel data was explained. The firm-specific and macroeconomic

independent variables were placed in two separate regression models because it is not

justifiable to place them in the same regression model, due to their varying natures. A dummy

variable was later constructed to indicate if an M-REIT was conventional, or Shariah-compliant

so that the impact of Shariah-compliance was examined. Therefore, Shariah-compliance was

also included as a firm-specific independent variable in the regression model.

Also, Chapter Four outlines the findings of the two phases of this study. Phase one

encompassed the unconventional way of identifying potential factors that would drive the share

prices of M-REITs by using a literature review and synthesis. The factors identified were


subsequently put through to a variable selection process which was made up of three stages.

Stage one was the identification of variables by reviewing past studies; stage two was the

elimination of variables depending on the significance of the variables analysed, while stage

three was the elimination of variables based on their added value to the analysis. The rationale

and theoretical justification of each of the chosen variables were discussed. After the

independent variables were selected, phase two of this study ran the panel data analysis through

EViews to find the relationships between the independent variables and M-REIT share prices.

The panel data analysis aimed to test the six hypotheses drawn up in Chapter Three (refer to

Para 3.5 Hypotheses).

In Chapter Five, the rationale behind the findings was discussed and explored, both the

empirical and theoretical justifications. The positive relationships of the MC, P/E ratio, IR and

Shariah-compliance and the negative relationships of the DY and IFR with M-REIT share

prices were discussed and justified. Lastly, Chapter Six includes a summary of the thesis, a

summary of the results, the contributions of the study, its limitations and recommendations for

future study and the conclusions of this research thesis.

6.2 Summary of Results

This thesis aims to identify and provide deeper insights into both the firm-specific and

macroeconomic factors that could cause an impact on M-REIT share prices and also examines

the relationships between the selected independent variables and the dependent variable.

There were 24 independent variables identified through the literature review and synthesis

(Phase One of the research, refer to Para 4.2 Phase One: Identification of Factors through

Literature Review and Synthesis). Among the 24 independent variables that could drive the

share price movements, 18 were firm-specific, namely; MC, NAV, DY, dividend payout ratio

(DPR), dividends per share (DPS), debt to asset ratio (D/A Ratio), debt to equity ratio (D/E

Ratio), NI, earnings per share (EPS), P/E ratio, retained earnings (RE), return on equity (ROE),

return on assets (ROA), size (represented by the logarithms of total assets), economic value

added (EVA), debt to capital ratio, first lag of share price and Shariah-compliance. On the

contrary, six of them were macroeconomic independent variables, namely; the IR, the IFR, the


exchange rate (ER), the money supply, crude oil price and gross domestic products (GDP). The

past studies which had focused on these factors, in general, analysed 16 of the firm-specific

independent variables and all of the six macroeconomic independent variables, whereas, those

studies carried out on REIT industries, which were more scarce, only analysed seven firm-

specific and two macroeconomic independent variables.

It was crucial to select appropriate independent variables to be included in the panel data

regression model. The 24 independent variables mentioned earlier were identified through a

literature review and synthesis, which was stage one of the variable selection process. The

second stage eliminated independent variables, based on the significance of the variables, as

analysed in past studies. At this stage, six independent variables, namely; the NI, RE, DPR,

size (represented by the logarithms of total assets), the crude oil price and GDP, were

eliminated from the panel data analysis because the past studies had unanimously agreed that

they had shown insignificant impacts on share price movements. At stage three of the variable

selection process, the independent variables were retained or eliminated based on their added

value to the analysis. Among the 18 variables which remained after the stage two elimination

process, nine independent variables, namely; NAV, ROE, ER, D/E ratio, D/A ratio, ROA, EVA,

leverage (represented by debt to capital ratio) and the first lag of the share price were concluded,

unanimously, by past studies to have significant impacts on share price movements. The

relationships between NAV, ROE, ROA, EVA, the debt to capital ratio, the first lag of the

share price and the share price, in general, or in REIT industry were positive, while the ER,

D/E and D/A ratios impacted share price movements negatively. Therefore, only MC, DY,

DPS, EPS, the P/E ratio, Shariah-compliance, the IFR, the IR and the money supply were

considered because past studies indicated varying results on their impacts on share prices.

The added value of the remaining nine independent variables with share prices was

subsequently examined. The inclusion of both the DY and DPS or the EPS and the P/E ratio in

the regression model would lead to the problem of multicollinearity (The Pennsylvania State

University 2017). Thus, based on theoretical justification, the DY and the P/E ratio were

included in the regression model while the DPS and the EPS were eliminated. According to

Karim (2013, p. 1068), Tan (2014) and MIDF Research (2017), the amount of money injected

into the economy or the money supply growth rate in Malaysia is highly related to the IR


targeting. Therefore, to avoid multicollinearity, the money supply was not selected as a

macroeconomic independent variable. Taking into consideration their theoretical relevance and

importance, the MC, DY, P/E ratio, IFR and the IR were included in the panel data regression

model. Shariah-compliance was later added, as a firm-specific factor, to evaluate if it was

significantly related to the share price movements of M-REITs.

The analysis was run through EViews and the findings indicated that all of the six independent

variables were significantly related to the movements of M-REIT share prices. According to

the results of the analysis, the MC, P/E ratio, IR and Shariah-compliance variables had a

positive relationship with M-REIT share prices while the DY and IFR variables were

negatively related to share prices. The results for the DY, P/E ratio and IR variables were

inconsistent with the hypotheses, but the rationale behind the findings was discussed in Chapter

Five Discussions. On the contrary, the results for the MC, IFR and Shariah-compliance

variables were consistent with the hypotheses. The significant positive relationship between

the Shariah-compliance dummy and M-REIT share prices indicated that, in general, the shares

of Shariah-compliant REITs were priced higher than those of conventional REITs.

6.3 Contributions of the Study

6.3.1 Extension of Research on the Factors that Drive the Share Price Movements of

REITs in the Malaysian Context

This thesis has offered more insights into, and a more holistic view of the factors that could

affect the share price movements of M-REITs significantly. The results of past findings, which

were proven to be controversial, were investigated and the relationship between each of the

factors and the M-REIT share prices was examined. This study carried out analyses on both

firm-specific and macroeconomic factors, and the impacts of Shariah-compliance were

explored as well, hence, more insights were provided. All of the past studies that have focused

on the REIT markets only carried out an analysis of firm-specific factors, macroeconomic

factors or the significance of Shariah-compliance. Singh (2018) was the only past research that

studied both firm-specific and macroeconomic factors which might drive share price

movements in general. However, the research concentrated on Omani financial organisations,


rather than REITs, and included firm-specific and macroeconomic independent variables

which had very differing natures in the same regression model, without any justification.

Furthermore, in the Malaysian context, most of the past studies only analysed the impacts of

one independent variable, be it firm-specific or macroeconomic, on M-REIT share prices. For

example, Ali (2006) only examined the relationship between market capitalisation (MC) and

share prices and the study included not only M-REITs but 30 real estate related organisations.

Besides, Hooi and Smyth (2011) and Wong (2015) only focused on the significance of IR

fluctuations on M-REIT share prices, whereas, Ong, Teh and Chong (2011, pp. 1-15)

investigated solely the relationship between NAV and M-REIT share prices. Also, NAV, NI

and MC were included as independent variables in the regression model of Olanrele (2014, pp.

492-502) but the study was only on a single M-REIT. By taking into account one regressor or

conducting analysis on just one REIT, the study offered less insight into the topic. Also, without

looking into both the firm-specific and macroeconomic aspects of the M-REIT market and

justifying the selection of variables, may not suffice to establish the reliability and validity of

the research. Furthermore, most of the past studies provided no reasoning for their findings.

Therefore, there was a lack of holistic understanding of the factors that drive the share price

movements of M-REITs.

In this study, not only was the identification of factors through a literature review and synthesis

carried out, but an extensive variable selection process was conducted as well so that the

regression model comprised only the independent variables that were believed to add the most

value to the analysis. The analysis results showed that the DY had a negative relationship with

M-REIT share prices, while the P/E ratio and IR were positively related to the share prices.

The hypothesis testing of these variables was rejected. The findings suggested that REITs do

not react like organisations in general. The negative relationship between the DY and M-REIT

share prices was claimed to be most relevant to investors’ confidence in M-REITs’ dividend

policies. Furthermore, the possible reasoning behind the positive relationship between the P/E

ratio and M-REIT share prices is because the complexity of a higher or lower P/E ratio is not

taken into account, or not well known, by the investors of M-REITs. Rather, they regard market

expectations of a higher or lower P/E ratio to be reliable. On the other hand, though REITs are

generally perceived to be IR sensitive and negatively related to IR, it is imperative to examine


the reason behind the fluctuation (Lloudis 2016). All of these findings indicated that the typical

perception of the relationship of an independent variable and share prices may not apply to M-

REITs.

6.4 Implications of the Study

6.4.1 Existing and Potential Investors: Reduction of Uncertainty

In reality, many Asian REIT markets, such as those in Japan and Singapore have outperformed

the REIT markets globally. Besides, the M-REIT market is believed to have much potential.

However, M-REITs’ performance and returns were below par, comparatively. The neutral

outlook of investors and investment analysts on the M-REIT market and their lack of

confidence in M-REITs are attributable to a lack of analysed and known near-term catalysts of

their share price movements (Wu 2011; Kaur 2017). This is claimed to be a major investment

deterrent. When potential investors are not well informed of the logical expectations

concerning the share price movements of M-REITs and are deprived of making rational

investment decisions, it increases their sense of uncertainty and diminishes their confidence.

This is of grave concern for the future of M-REITs because, based on studies, investors in

Malaysia are generally prone to avoid risk and uncertainty, which is true for investors who are

attracted to REITs, in general (Ung 2012; Rao 2019). Also, according to Kaur (2017), Asian

REIT markets were expected to expand another 10 per cent and account for 35 per cent of the

REIT markets globally by 2020. If investors’ confidence in M-REITs is not improved, M-

REITs may lose out on the opportunities in such a growing market. Therefore, it is crucial to

reduce the knowledge gap concerning the factors that affect the share price movements of

REITs in Malaysia. This study is believed to have reduced the knowledge gap.

6.4.2 Standard Setters: Motivation to Enhance the Spread of Shariah-compliant REITs

There has been a perception proliferated that Shariah-compliant REITs are deemed to have

more favourable performance and share price movements than conventional REITs. However,

Miniaoui, Sayani and Chaibi (2015, p. 357) claimed that this could be misleading and that

Shariah-compliance is not equivalent to lower risk and higher return. According to the

Malaysia International Islamic Financial Center (MIFC) (2013), regardless of the belief, or

typically held perception, the spread and development of Shariah-compliant REITs have


proven to be challenging around the globe because of the lack of distinct regulatory framework

and standards that aimed at facilitating their governance and operations. However, the M-REIT

market was the first to introduce a Shariah-compliant REIT and, in comparison, has offered

more clear cut guidelines to enhance the growth of the market (Islamic Markets 2018).

Therefore, the Shariah-compliant M-REIT market is believed to have great potential to grow

(Malaysia International Islamic Financial Center (MIFC) 2013; Nordin 2018).

According to Ting and Noor (2007) and Ahmad Tajjudin Rozman et al. (2015, pp. 8-9), it is

imperative to identify and examine the relationship between Shariah-compliance and M-REIT

share prices because the Shariah-compliant M-REIT market is claimed to potentially play a

vital role in strengthening the competence of Islamic financial instruments in Malaysia. The

findings of this research paper support the widely held perception that Shariah-compliance has

positive and significant impacts on M-REITs’ performance and share prices and, therefore, acts

as a motivation for the government and regulators to offer privileges and set standards that

further enhance the spread and development of Shariah-compliant M-REITs. Based on the

belief described above, when the Shariah-compliant M-REIT market becomes more prominent,

it increases the likelihood of other Islamic financial instruments in Malaysia to become more

competent too.

6.4.3 Industry Development and Growth: Becoming More Attractive

As mentioned above, when investors have a more holistic view of the factors that affect the

share price movements of M-REITs, their uncertainty about the future of M-REITs will be

reduced. The enhancement of investors’ confidence will, in turn, welcome more investments

into the REIT industry in Malaysia. Besides, the standards setters in Malaysia are said to be

envigorated to provide more clear-cut guidelines and a regulatory framework to enhance the

governance and operation of Shariah-compliance M-REITs, because the results of this research

indicate that Shariah-compliance is positively and significantly related to M-REIT share prices.

This may motivate real estate companies to invest in the establishment of Shariah-compliant

M-REITs; as well as for investors, in general, who are becoming more inclined towards ethical

decision making, rather than merely profit-making, to make more informed and confident

decisions to invest in Shariah-compliant M-REITs (Mohamed & Lusyana 2017, p. 61).

Therefore, the development and spread of the Shariah-compliant M-REIT market will engage


more investments in M-REITs. With the surge of the attractiveness of M-REITs as an

investment instrument, further development and expansion of the industry is expected. This

will, in turn, lead to a rise in economic activity and job creation. According to Atchison and

Yeung (2014), the Association for Real Estate Securitisation (ARES) reported in 2012 on the

rise of GDP growth and job creation in Japan and France which were attributable to the spread

of REITs in their countries. REITs in Japan and France directly created employment

opportunities for 83,000 and 66,300 people, respectively, as of 2012. Moreover, the estimated

number of jobs created by the REIT industry in Japan by 2020 amounts to 128,000 (Atchison

& Yeung 2014). In the same way, the increase of M-REITs’ attractiveness is expected to boost

the development and growth of the industry, leading to GDP growth and job creation in

Malaysia.

6.5 Limitations and Recommendations

However, there are limitations to this study. Although this research thesis intended to analyse

the entire population of M-REITs, only 17 M-REITs were included in the analysis while there

were 18 M-REITs as of 2017. Data regarding the KIP REIT was not gathered because it was

newly established in 2017 and its data and information were very limited. Moreover, the

additional disturbances or noise caused by the unbalanced panel data could be better justified

if deeper research was carried out in this area. REITs are also perceived as financial instruments

which are more resilient against shocks, hence, some past studies which have concentrated on

the comparison of impacts of the 2008 GFC on stocks, in general, and REIT share prices found

that REITs and, especially, M-REITs and Shariah-compliant REITs outperformed the

conventional stocks. The effects of the GFC on M-REIT share prices were not analysed in this

study. Therefore, it is suggested that future studies include the KIP REIT in their analyses,

provide a stronger justification for the additional disturbances caused by unbalanced panel data

and investigate the resilience of M-REITs against shocks and volatility by examining their

performance and returns during the pre-GFC, GFC and post-GFC periods.

6.6 Conclusion

This thesis has increased the knowledge of potential investors and other stakeholders on both

the firm-specific and macroeconomic factors driving the share price movements of M-REITs.


When they have more confidence to invest in M-REITs, knowing what to expect, it is more

likely for M-REITs to grab hold of the opportunities offered by the continuous growing Asian

REIT market. The findings also justified that Shariah-compliance would impact the share

prices of M-REITs favourably. It is believed that the Malaysian REIT market, being the pioneer

of Shariah-compliant REITs, has an advantage to steadily expand as well. This study is

expected to continue to help both existing and potential investors of M-REITs to make more

informed investment decisions.

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