Report on Fama French Three Factor Model

Internship report

on

Test of the Fama-French Three Factor Model in Bangladesh

Supervised by:

Md. Sajib Hossain

Lecturer

Department of Finance

Faculty of Business Studies

University of Dhaka

Submitted by:

Mohammad Mominuzzaman Bhuiyan

ID: 16-174



University of Dhaka

Date of Submission: 22nd May, 2014.

Test of Fama-French Three Factor Model in Bangladesh

Certification by Supervisor

This is to certify that the internship report on “Test of the Fama-French Three Factor Model

in Bangladesh” in the bona fide record at the report is done by Mohammad Mominuzzaman

Bhuiyan a partial fulfillment of the requirement of Bachelor of Business Administration degree

from the Department of Finance, Faculty of Business Studies, University of Dhaka.

The report has been prepared under my guidance and I wish his success.

________________________________

Md. Sajib Hossain

Lecturer



University of Dhaka

Date…………

Page | 2


Declaration

I do hereby declare that the internship report on “Test of the Fama-French Three Factor

Model in Bangladesh” has been prepared by me under the guidance of Lecturer Md. Sajib

Hossain for the partial fulfillment of BBA program from the department of Finance, Faculty of

Business Studies, University of Dhaka.

I further affirm that the work reported in this internship is original and is no part or whole of the

report has been submitted by any other students for the completion of BBA or other degree.

_______________


ID: 16-174



University of Dhaka.

Page | 3


Letter of Transmittal

22nd May, 2014

Md.Sajib Hossain

Lecturer



University of Dhaka

Subject: Submission of internship report on “Test of the Fama-French Three Factor Model in

Bangladesh”.

Dear Sir,

Here is the report on “Test of the Fama-French Three Factor Model in Bangladesh” which you

asked me to conduct.

I would like to thank you for giving me to prepare such a report. It has helped me to know about

the factors that are influencing our stock market returns. While preparing this report, I had to

collect information from Dhaka Stock Exchange and other secondary sources as your

instructions. After that I analyzed the information to find the effect of size and value factor to

stock market returns and came out with some results. This helped me to know about some insight

information about our stock market. I have tried my level best to present all the things to make

the report more informative and usual one. If any part of the report means inappropriate and

irrelevant with the subject, please advise me.


ID: 16-174



University of Dhaka.

Page | 4


Acknowledgement

I would like to express my deepest gratitude to my supervisor Md. Sajib Hossain for his deep

patience, inspiration and scholar guidance during the works.

I would like to show my gratitude to my friends especially Saleh Sadiq and Annonya, who

helped me a lot through sharing the knowledge on the topic. I wish to thank all my well wisher

for their immense suggestions during conducting my study.

I would like to express many special thanks to my parents and family, who were always there to

give me all sorts of support and understanding.

At last, I am the responsible for any errors.

Page | 5


Contents

1. Introduction.............................................................................................................................................7

2. Motivation of the study............................................................................................................................8

3. Literature Review....................................................................................................................................9

4. Overview of the Bangladeshi stock market...........................................................................................13

5. Data......................................................................................................................................................15

6. Methodology.........................................................................................................................................16

7. Empirical analysis.................................................................................................................................18

7.1.1. Equal weighted portfolio (with financial institutions):.................................................................20

7.1.2. Equal weighted portfolio (without financial institutions):............................................................23

7.1.3. Portfolio index for equal weight..................................................................................................25

7.2.1. Value weighted portfolio with financial institutions....................................................................26

7.2.2. Value weighted portfolio without financial institutions...............................................................28

7.2.3. Portfolio index for value weight..................................................................................................30

8.Conclusions...........................................................................................................................................30

9. References.............................................................................................................................................32

Page | 6


1. Introduction According to Fama & French (2004), the Capital Asset Pricing Model (CAPM) offers powerful

predictions about how to measure risk and the relation between expected return and risk. A vast

amount of researches has been conducted to test the validity of the CAPM in explaining the

variation in rate of return. However, these studies provide no evidences to support this model.

Motivated by the weakness and limitations of the CAPM, in 1993 Fama & French came up with

a model for explaining stock returns using three factors: market, book to market, and size. They

claim that the behavior of stock returns in relation to market, size and value factors is consistent

with the behavior of earnings. They admit that their findings are weak, especially relating to the

value factor, but attribute this to the measurement error problems in earnings data. There is a

burgeoning research literature contradicting, confirming, criticizing, and extending the Fama-

French

In this paper, I have examined the Fama-French three- factor model for the Bangladeshi stock

market for the period January 2002 to December 2013 in which time the market got the taste of

expansion and the pain of contraction. I have analyzed whether the market, size and value factors

can explain the cross-section of stock returns better than its variant including the one factor

model (CAPM).

I have tested three factors model for both listed securities with and without financial institutions

and the empirical result do not support the model. All three factors, market, size, and value have

no influence on random returns in the Dhaka stock market whereas only the market factor has

influence on stock returns significantly. This result is not consistent with the results of the prior

study of the three factor model in Bangladesh (Rahman (2006)). They found that the stocks

returns are determined not only by market beta, but also by other variables such as; firm market

capitalization, firm sales, book to market value. They used data for the period of 1999 to 2003 of

non financial firms listed in Dhaka stock exchange. These variations in the results may be for the

variations in the different time period.

I have divided the work into the following parts. The first is the literature review where prior

research on the topic is discussed and analyzed (section 2). An overview of the Dhaka Stock

Exchange of the last 10 years is explained in section 3 to get brief information about the financial

performance of the market before starting the main work. The sample securities and sources of

Page | 7


data, methodology, and variables are contained in section 4. Section 5 incorporates the empirical

results of test of Three Factor Model and section 6 contains the conclusion of the paper.

2. Motivation of the study Fama- French stated in their different articles that size factor that is small size companies

outperform big size companies and value factor that is value firms (higher BE/ME) generate

higher returns than that of growth firms ( low BE/ME). Many articles have been written on

applicability of three factor model for stock returns for different countries. Some articles find

consistency with this model but some articles got inconsistency with this model for different

countries.

One of the motivations of this study is to see whether the results of the prior study of the three

factor model in Bangladesh (Rahman (2006)) are consistent with my study. Besides there are

very few researchers in our market that are needed for the improvement of the capital market

technically to sustain in the long run without experiencing consistent underperforming of

securities . I hope that my report will encourage more people to experiment more theories in our

market to find the main problems of it not performing well for the last few years at a continual

basis.

Page | 8


3. Literature ReviewThe capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965) was the most

widely recognized explanation of stock prices and expected returns. It gives a prediction of risk

of an asset or a portfolio and its expected return which thereby helps in evaluating potential

returns of investments. The empirical evidence of the failures of CAPM was grave. The problem

with CAPM is that it is based on many unrealistic assumptions. Roll (1976) claimed that any

valid test of the CAPM presupposes complete knowledge of the true market portfolio’s

composition. This means that every individual asset must be included in a test for obtaining

correct results. This is difficult and infeasible and could lead to ambiguities in tests. Fama and

French (1992) found that the cross section of average stock returns for the period 1963-1990 for

US stocks is not fully explained by the CAPM beta and that stock risks are multidimensional.

Two of these dimensions of risk, they suggest, are proxied by size and the ratio of book value of

common equity to its market value (BE/ME). Fama and French (1993) identify a model with

three common risk factors in the stock returns - an overall market factor, factors related to firm

size (SMB) and those related to book-to-market equity (HML). In order to identify the most

important proxies for risk factors, the authors used the Black, Jensen and Scholes (1972) time

series regression model. They found that both firm size and book to market value of equity ratio

have a strong role in determining the cross section of average returns. The resultant model was

highly popularized and became known as the Fama and French Three-Factor-Model (TFM).

Specifically, they discovered a negative relation between cross section of average returns and

firm size, and a positive relation between cross section of average returns and book to market

ratios. In other words, small firms and value firms (high book to value ratio) are risky so

investors are compensated with high rates of return. Interestingly, Fama and French also found

that once one considered the size and value factor loadings of a diversified US stock portfolio,

the market loading (beta) did not explain returns.

Many studies have been conducted to test the ability of the Fama & French three factor model to

explain and predict the variation in the stocks rate of return. These are followings:

Daniel and Titman (1997) used monthly data over the period from July 1963 to December 1993

for NYSE, AMEX, and NASDAQ stock markets, the finding of Daniel and Titman did not

support the Fama & French three factor model, they indicate that the size and book to market

Page | 9


equity ratio are both highly correlated with stocks average rate of return. They conclude that the

characteristics of these stocks not their risk explain the cross –section stocks return, they also

concluded that investors like growth stocks (strong firms) and dislike value stocks (weak firms).

They also reported that market beta factor has no explanatory power for stock rate of return.

As a response to Daniel and Titman (1997), Davis et al(2000) extended the data set from 1929 to

1997, they indicated that the results of Daniel and Titman (1997) are specific to relatively short

data set that they used and the three factor model explain the value premium better than

characteristic explanation. They also observed that the value effect is strong in the US stock

markets and the relation between average stocks rate of return and book to market equity is

positively significant.

Drew and Veeraraghavan (2003) used data from four Asian emerging markets Hong Kong,

Korea, Malaysian, and Philippines over the period from 1991 to 1999 in order to investigate the

ability of the Fama & French three factor model to explain the variation in stocks average rate of

return, they stated that the three factors model have superior power in explaining the average

stocks return in all four countries.

Basu (1977) studied the possible influence of earnings to price ratio (E/P) and found that stocks

with high E/P ratios systematically generate higher returns than those implied by the CAPM.

Using daily data from Australian stock market Faff (2004) provides a test for FF three factor

models. Using a sample from the industrial sect, the results show that the FF provides a

convenient assessment to the risk premium. The results also indicate that the three factors model

still better than the CAPM in explaining the excess rate of return. Other studies tested the

validity of the assets pricing models in Emerging Markets.

Petkova (2006) used monthly data over the period from July 1963 to December 2001, he

investigates the ability of Fama & French three factor model in capturing the investment

opportunity that appears in stock markets, for more specification both factors SMB and HML

provide superior prediction to the excess market return and variation in this return and both

factors highly correlated with these opportunity and provide better explanation to the time- series

variation to the stocks rate of return, but not for cross section return. He concluded that the

Intertemporal capital assets pricing model (ICAPM) that was developed by Merton (1973)

provide better explanation to the cross- section over than Fama & French three factor model for

his specific sample and period.

Page | 10


Tony and Veeraragavan (2005) compared the performance of the CAPM with the TFM for

equities listed in the Shanghai Stock Exchange as well as simultaneously investigating the

explanatory power of idiosyncratic volatility. They find that firm Size, BE/ME, the Market factor

as well as idiosyncratic volatility are priced risk factors Their results are consistent with the

findings of Fama and French (1996).

Chan, Hamao and Lakonishok (1991) find a strong relationship between BE/ME and average

return in Japanese stocks

Rosenberg, Reid and Lanstein (1985) find a positive relationship between the average return and

the ratio of a firm’s book value to market equity (BE/ME).

Lakonishok, Sheifer and Vishny (1994) find a strong positive relationship between average

returns and BE/ME and cashflow/price ratio (C/P). These relationships could not be explained by

the CAPM.

Banz (1981) who claimed that ‘size effect’ was present for more than 40 years and that the

CAPM was misspecified.

Kothari, Shanken and Sloan (1995) present evidence contrary to Fama and French’s claim for the

BE/ME factor effect. They doubt the explanatory power of BE/ME, although find an evident size

effect. Financial distress is higher for firms with high book-to-market ratio. They owe a

substantial part of the risk premium to selection bias in the data used since there is an

overestimation of returns for these distressed firms.

Bundoo (2006) studies the emerging African stock markets for evidence of size and value

premium, and finds that the three factor model holds for the stock exchange of Mauritius. Even

after taking into account the time-varying betas, the results for size and BE/ME effects are

statistically significant. But they caution that the results may be sample specific and this model

should be tested across other stock exchanges for checking robustness.

Gaunt (2004) studies the evidence of size effect, BE/ME effect and the application of the Fama

and French three factor model in the Australian market. He finds that the betas are less than one

which is contrary to Fama and French who find beta to be close to one. Risk tends to be greater

for smaller size firms and low BE/ME ratios like the findings of Fama and French. There is

evidence that there is a monotonic increase in the HML factor loading from low to high BE/ME

portfolios implying that the HML factor plays a significant role in asset pricing. His sample

study finds an inconsequential small firm effect and no large firm effect. He finds an

Page | 11


improvement in the explanatory power of the three factor model over and above the one factor

CAPM when compared to prior studies in the Australian setting.

Nartea and Djajadikerta (2005) find a significant size effect and a weak BE/ME effect in the case

of New Zealand. According to them, the three factor model’s explanatory power is not as big an

improvement over the CAPM as is for the Australian case.

The French case examined by Ajili (2005) also provides evidence for the three factor model

being of higher explanatory power than the CAPM. In the three factor regression, he finds the

intercept to be close to zero implying that the model is a good explanation of the cross-section of

average stock returns.

Connor and Sehgal (2001) empirically examined the application of the TFM in the Indian

market. They also find evidence for pervasive Market, Size and BE/ME factors in the Indian

market and produce largely consistent results supporting the TFM.

Bhandari (1988) found that firms with high leverage (book value of debt to market value of

equity ratio) produce high returns relative to their betas.

Bhandari (1988) found that firms with high leverage (book value of debt to market value of

equity ratio) produce high returns relative to their betas.

Page | 12


4. Overview of the Bangladeshi stock marketDhaka Stock Exchange is one of the two stock exchanges of Bangladesh. It was first

incorporated as East Pakistan Stock Exchange Association in 28 April 1954 and started trading

in 1956. It was renamed as Dacca Stock Exchange Ltd in 13 May 1964. The trading was

discontinued for five years after Liberation War in 1971. Again though trading was restarted in

1976, DSE was started on 16 September 1986 (Wikipedia). The total market capitalization of

listed companies stood at over $50 billion on the Dhaka Stock Exchange.

Over the last three decades the market experienced both bullish and bearish. The listed securities

in the Dhaka Stock Exchange are increasing for the financial year 2003 to 2013. In 2003 the

numbers of securities were 267 and that number became 529 at the end of year 2013. At the

same time total market capitalization of all listed securities has been increasing for the last 12

years. In year 2003 the total market capitalization were about tk. 97.59 million and it became tk.

2385.247 million at the completion of year 2013

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 20130

100

200

300

400

500

600

05001000150020002500300035004000

267 256 286 310350

412 415 445501 515 529

97.59 224.92230 315.45742.2

1059.53

1887.177

3471.10899999999

2055.452385.246999

99999

2635.78499999999

No of listed securities Market cap(tk.bn)

Figure : DSE trading statistics

The time between 2003 and 2008 the market saw a steady growth and turnover. From 2008 to

2010 the capital market under the influence of investor’s optimism. That was reflected in both

increase of turnover, market P/E ratio and growth .We see turnover of the market increased at an

increasing rate from year 2008 to 2010 and the market saw its highest turnover in 2010. The total

value of that turnover in 2010 was about tk.400000 million. But after year 2010 market saw its

lowest turnover in its history and its now still continuing .within the time period market saw a

ups and downs of equity index and it reached its highest position in year 2010 and at the end of

Page | 13


the year 2010 the market equity index has been decreased at an increasing rate which indicates

that market entered into the bearish in case of share prices for the loss of investors’ confidence.

In 2010 equity index was about 8800 whereas it was only about 1000 in year 2003. But in 2013

market saw 4000 equity index.

Figure : DSE trading statistics

Now market saw steady growth in P/E for the year 2003 to 2008 and after 2008 that growth

reached its maximum point in year 2010. But after 2010 it also decreased in line with turnover

ratio and equity index. In year 2010 the P/E ratio was 34 times whereas it was only 5 times in

year 2003. But in 2013 the P/E ratio was 15 times. Figure 1 shows the market expansion in the

period of 2008 to 2010 and market contraction in the period of 2010 to 2013.

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

0.01000.02000.03000.04000.05000.06000.07000.08000.09000.0

0

5

10

15

20

25

30

35

Equity indexP/E

Figure: The DSE trading statistics

Page | 14

2003

2005

2007

2009

2011

2013

0.00100,000.00200,000.00300,000.00400,000.00500,000.00

Turnover(tk.mn)

Turnover(tk.mn)


5. Data I have obtained monthly stock prices and other accounting information such as dividend , face

value , market capitalization , price earnings ratio , net asset value(NAV) etc of all the listed

companies from Dhaka Stock Exchange for the financial year 2002 to 2013 . Monthly data are

used because they account for speed in arbitrage adjustments and in the same time mitigate any

potential problems that are associated with microstructure issues such as bid-ask spreads. I have

considered both active and dead equities in order to address the survivorship bias. I have

eliminated all equities with unavailable market data for at least two months in a year for that

particular year. I have omitted stocks with negative book value of equity in order to prevent

distortion of the results.

It is assumed that dividends are re-invested to purchase additional units of equity at the closing

price applicable on the ex-dividend date. I have calculated index adjusted price by the inclusion

of the dividend, split and closing prices to determine return index and the calculation ignores tax

and re-investment charges. Market Value is the share price multiplied by the number of ordinary

shares in issue5. Then I have calculates Market Value to Book Value and calculated its inverse

(Book to Market Value), which is the variable of interest. It is defined as the balance sheet value

of common equity divided by the market value of common equity.

Finally, I have taken the 91 days Treasury bill rate of the last 13 years of Bangladesh government

as a proxy for risk free rate

Page | 15


6. Methodology My work follows the Fama and French (1993) methodology which use the time series regression

approach of Black, Jensen and Scholes (1972). However, I have included both financial and non-

financial firms and do not study the bond market. Monthly portfolio returns are regressed on

market return and mimicking portfolios for size and book to market value. As a result, the

mimicking (zero investment) portfolios act as risk factors and the time series regression slopes as

factor loadings.

Firstly I have classified the market on size and BE/ME. I have divided the market as small

capitalization and big capitalization based on market capitalization. Market have been classified

as Low BE/ME, Medium BE/ME, High BE/ME and I have classified the market in this way

because according to Fama and French (1993) stocks are sorted into two groups on size and

three groups on BE/ME and the latter has a stronger role in average stock returns than the

former.

I have constructed six intersecting portfolios (SL, SM, SH, BL, BM, BH). I have calculated

monthly return of each portfolio for both equal weight and value weight. Portfolio SL consists

of small and growth (low BE/ME) equities, portfolio SM consists of small and medium BE/ME

equities, portfolio SH consists of small and value (high BE/ME) equities, portfolio BL consists

of big and growth (low BE/ME) equities, portfolio BM consists of big and medium BE/ME

equities, portfolio BH consists of big and value (high BE/ME) equities.

Besides I have constructed equal weighted and value weighted return index for value stock,

growth stock, small size, medium size and large size companies for both listed companies and

companies without financial institutions.

For regression analysis I have used the following equation

𝑅𝑝𝑡−𝑅𝑓𝑡=𝛼𝑝𝑡+𝑏𝑝 𝑅𝑚𝑡−𝑅𝑓𝑡 +𝑠𝑝𝑆𝑀𝐵𝑡+ℎ𝑝𝐻𝑀𝐿𝑡+𝜀𝑝𝑡

Where

p is portfolio p (SL, SM, SH, BL, BM or BH)

t is month t (January’ 02 – December ’13)

The dependent variable 𝑅𝑝𝑡−𝑅𝑓𝑡 is the excess return of portfolio p and the first risk factor 𝑅𝑚𝑡−𝑅𝑓𝑡 is the excess return of the market. The other two risk factors are formed from the

six portfolios presented above. SMB (Small minus Big) is the difference between the average

monthly return of the three small capitalization portfolios and the average monthly return of the

Page | 16


three big capitalization portfolios. HML (High minus Low) is the difference between the average

monthly return of the two high BE/ME portfolios and the average monthly return of the two low

BE/ME portfolios.

𝑆𝑀𝐵 = ((𝑆L+𝑆𝑀+𝑆H) – (𝐵L+𝐵𝑀+𝐵H))/ 3

𝐻𝑀𝐿 = ((𝑆H+𝐵H) – (𝑆L+𝐵L))/ 2

In other words, the risk factors related to size and value is not tradable variables so zero

investment portfolios are constructed. I have taken a long position in small firms and a short

position in big firms for the SMB factor and for the HML factor I have taken a long position in

value firms and a short position in growth firms. SMB measures a small size premium and HML

a value firm premium as a consequence.

Page | 17


7. Empirical analysisTable 1 summarizes the number of companies in each portfolio for each year of the sample

period. Small stock portfolios have almost the same number of companies with big stock

portfolios (the division point is the median) is expected. High, medium and low BE/ME stock

portfolios are also equally divided in three parts (the division points are the 33.33% and 66.67%

percentiles). It is observed that small size companies tend to have higher BE/ME ratios and in

contrast, big size companies tend to have lower BE/ME ratios. On average, there are only 34 SL

companies whereas

Year SL SM SH BL BM BH Total

2002 33 19 46 33 46 19 196

2003 32 35 85 69 66 16 303

2004 29 20 61 44 53 12 219

2005 24 24 55 45 44 13 205

2006 31 22 56 42 50 16 217

2007 37 17 69 45 65 12 245

2008 39 20 68 46 65 16 254

2009 31 33 43 41 35 28 211

2010 36 17 69 46 64 12 244

2011 31 19 44 32 44 18 188

2012 40 39 33 35 35 41 223

2013 41 42 32 36 34 44 229

Average 34 26 55 43 50 21 228

Table 1: No of companies in six portfolios

on an average 55 SH companies are found in our market over the years. The opposite happens in

big size portfolios where there are only 21 BH companies and 43 BL, 50 BM companies. Under

the assumption that high BE/ME ratios are signs of distressed firms, the above finding indicates

that, on average, small size firms tend to be distressed and are not expected to have an adequate

earnings generation capability. On the other side, most big size firms listed in the Dhaka Stock

Exchange (DSE) have low and medium BE/ME ratios and consequently are expected to be

profitable in the future.

Page | 18


Portfolio Average m cap (tk.in millions)

SL 6098.842917

SM 9450.99

SH 8607.70625

BL 301179.08

BM 190544.4833

BH 104210.3575

Table 2: Average market capitalization in six portfolios

Table 2 presents further insights in the size and BE/ME ratio of firms listed in DSE. Small size

companies with large BE/ME ratio has the highest average market capitalization that is about tk.

8608 million .The average market capitalization of all small size companies is about tk. 8052.513

million which is much lower than that of all big size companies ( about tk. 198644.6). Among

the big size companies big size portfolio with low BE/ME ratio has the largest market

capitalization that is about tk. 301179.1 millions. All of this above findings is based on equal

weighted portfolio which includes all listed companies including financial institutions except

mutual funds and corporate bonds

7.1.1. Equal weighted portfolio (with financial institutions):

Table 03: mean return and standard

deviation for six portfolio with financial institutions

Table 3 and its respective chart summarize the descriptive statistics for the dependent variables

(six portfolios) and the explanatory variables (factor portfolios) in the time series regressions.

Page | 19

Portfolio Mean Std.Dev

SL 0.0644982 0.373568

SM 0.0384975 0.115844

SH 0.0273382 0.110981

BL 0.0484295 0.072645

BM 0.0331618 0.074806

BH 0.0193043 0.092628


It is evident that the three small size portfolios have higher average returns than the three large

size portfolios confirming the inverse relation between the size and average return of the

portfolios (Fama and French (1992), Connor and Sehgal (2001)). The average returns are

0.04344 for the small size portfolios and 0.03363 for the big size portfolios.

SL SM SH BL BM BH

00.010.020.030.040.050.060.07

Mea

n re

turn

Figure1: mean return and standard deviation for six portfolio with financial institutions

Table 4 summarizes that two of them have negative mean values. In specific, the mean excess

market return is -0.0331426 and is in line with the fact that the sample period is characterized by

intense bear market rallies. The negative value of HML factor means that on average there is a

negative value effect that is not consistent with the portfolio returns and Fama and French

(1993). The negative value of market risk premium (-.2850045) indicating its inconsistency with

the three factor model. But there is positive value for SMB (0.0098128) that indicates that small

firms outperform big firms and return also depends on market risk premium.

Mean Standard deviation SMB 0.0098128 0.1437119HML -0.0331426 0.1912451

Rm-Rf (DGEN) -0.2850045 3.990607Rm-Rf (DSE20) 0.0013008 0.0902934

Table 04: Mean return and standard deviation of size and value factor

Page | 20


Portfolio Coef. p-value R-squaredSL Rm-Rf -0.00286 0.097 0.953

SMB 1.173161 0HML -1.151724 0

_cons 0.014 0.047SM Rm-Rf -0.0040929 0.079 0.1066

SMB 0.3097689 0.002HML 0.2616757 0.001

_cons 0.0429639 0SH Rm-Rf -0.003298 0.014 0.6832

SMB 0.9246724 0HML 0.6438719 0

_cons 0.0386642 0BL Rm-Rf -0.0031838 0.022 0.1995

SMB -0.3191893 0HML -0.1857632 0

_cons 0.0444975 0BM Rm-Rf -0.0043213 0.004 0.1245

SMB -0.2025076 0.002HML -0.0790541 0.095

_cons 0.0312973 0BH Rm-Rf -0.0027458 0.155 0.0338

SMB -0.0707005 0.387HML 0.0186414 0.761

_cons 0.0198334 0.013

Table 05: regression analysis for equal weighted portfolios

Interpretation:

In portfolio SL the p- value for market risk premium is 0.097 which is greater than 0.05

indicating its influence on market return and other two factors SMB and HML have no impact on

market return. As p-value for market risk premium in SM portfolio is 0.079 higher than 0.05 it

keep impact on return. In portfolio SH and BL, size factor and value factor have no impact on

return whereas market factor has insignificant impact since its p- value are lower than 0.05. in

portfolio BM only value factor has significant impact on return as its p-value is greater than 0.05

whereas market factor and size factor have insignificant impact on return since their p-value are

lower than 0.05.finally in BH portfolio all three factors have significant impact on return as they

have p- value that are larger than 0.05.

Page | 21


7.1.2. Equal weighted portfolio (without financial institutions):

Portfolios are here constructed based on the listed companies excluding financial institutions.

Table 06 shows us that the average mean return of the three small size portfolios is greater than

that of three big size portfolios that is also consistent with the previous result for all listed

companies including financial institutions. The average returns for small companies are .031374

and 0.029103 for the big size companies.

Portfolio Mean Std.Dev

SL 0.0329458 0.0934127

SM 0.0323059 0.1025278

SH 0.0288699 0.1328998

BL 0.043521 0.1258

BM 0.0353934 0.0742737

BH 0.0183931 0.0876286

Table 06: Mean return and standard deviation of equal weighted portfolio (without financial

institutions)

Table 07 summaries that that three of them have negative mean values .the negative value -

1385.71 of SMB means that there is a large size effect where big size companies have greater

returns and negative value -2085.71 of HML indicates that the growth companies have higher

returns that is inconsistent with the three factor model. Lastly the negative mean value of market

risk premium implies that market return is lower than risk free rate.

Table 07: Mean return and standard deviation of size and value factor

Page | 22

Mean Std.DevSMB -1385.71 16628.5HML -2078.579 24942.74

Rm-Rf (DGEN) -0.2850045 3.990607Rm-Rf (DSE20) 0.0013008 0.0902934


Portfolio Coef. p-value R-squaredSL Rm-Rf (DGEN) -0.0030476 0.12

SMB 0 0.0171HML -3.46E-08 0.912_cons 0.0320053 0

SM Rm-Rf(DGEN) -0.0034895 0.104SMB 0 0.0195HML 1.18E-07 0.732_cons 0.0315563 0

SH Rm-Rf(DGEN) -0.0031157 0.264SMB 0HML -1.90E-07 0.671 0.01_cons 0.0275867 0.015

BL Rm-Rf (DGEN) -0.0038387 0.185SMB 0 1HML -2 0_cons 0.0126153 0.277

BM Rm-Rf (DGEN) -0.0037214 0.016SMB 0HML -1.31E-07 0.595 0.0421_cons 0.0340613 0

BH Rm-Rf(DGEN) -0.0037706 0.039SMB 0 0.0311HML -1.37E-07 0.639_cons 0.0170339 0.021

Table 08: regression analysis for equal weighted portfolios (without fin institutions)

Interpretation:

Here in case of equal weighted portfolio for all securities without financial institutions we see

that the size factor has no any impact on the return. For all the six portfolios the p- value for the

value and market factor are greater than benchmark value 0.05 except portfolio BM and BH

where the p-value for value factor are greater than 0.05 whereas that value are insignificant for

market factor .

Page | 23


7.1.3. Portfolio index for equal weight

I notice from the equal weighted return index for all listed value stock, growth stock, small size,

medium size and large size companies with financial institutions that growth stock companies

are outperforming value stock (figure 02). Again large size companies are outperforming small

and medium size companies. These two results are not consistent with the findings of Fama –

French three factor model where it is stated that small and value size companies outperform

market.

value stock

growth stock

small size medium size

large size0

0.0050.01

0.0150.02

0.0250.03

0.0350.04

0.045

Mea

n re

turn

Figure 02: portfolio index with financial institutions

Figure 03 summarizes the equal weighted mean return for all companies without financial

institutions and it is seen that it also shows the same result that growth firms and large firms

performing well in the market.

growth stock

value stock

small size

medium size

large size

00.005

0.010.015

0.020.025

0.030.035

0.040.045

Mea

n re

turn

Figure 03: portfolio index without financial institutions

Page | 24


7.2.1. Value weighted portfolio with financial institutions

Table 09 represents the mean return and standard deviation for the six value weighted portfolio.

for the size effect we see that here the average mean return for the small size companies is

greater than that of the big size companies . The average mean return is 0.03350977 for the small

size companies whereas the average mean return for the big size companies is 0.03092223 that is

consistent with equal weighted portfolio return.

Portfolio Mean Std.

SL

0.040802

6

0.094035

1

SM

0.033410

8

0.082207

1

SH

0.026315

9

0.090454

7

BL 0.048947

0.076407

3

BM

0.030877

8

0.069268

6

BH

0.012941

9

0.090872

5

Table 09: mean return and standard deviation for six portfolio with financial institutions

For the value effect we see that the value premium is 0.252459 that indicates that value firms

have higher return than that of growth firms and these two results are fully consistent with the

findings of Fama and French (1992) and Connor and Sehgal (2001).

Table 10 shows that two of them have negative mean return. Negative value -.0252459 of HML

means that the market has growth firms effect and negative value of market risk premium refers

investors will get lower market return than treasury bill rate .on the other hand size factor has

the positive mean return that implies small size companies outperform large size companies

consistent with the three factor model.

Page | 25


Mean Std.DevSMB 0.0025875 0.0779803HML -0.0252459 0.0576353

Rm-Rf -0.2850045 3.990607

Table10: Mean return and standard deviation of size and value factor


SMB 0.7265069 0HML -0.3681464 0.001_cons 0.0289978 0

SM Rm-Rf -0.0039285 0.012 0.2082SMB 0.3525558 0HML 0.2945428 0.007_cons 0.0388149 0

SH Rm-Rf -0.0031025 0.019 0.5338SMB 0.7309713 0HML 0.4675791 0_cons 0.0353447 0

BL Rm-Rf -0.0031627 0.024 0.2698SMB -0.375605 0HML -0.4189634 0_cons 0.0384404 0

BM Rm-Rf -0.0038082 0.003 0.2711SMB -0.4342915 0HML 0.0676279 0.437_cons 0.0326235 0

BH Rm-Rf -0.0022734 0.153 0.3257SMB -0.3800695 0HML 0.7453111 0_cons 0.0320935 0

Table 11: regression analysis for value weighted portfolios (with fin. institutions)

Interpretation:

From the above regression analysis for value weighted portfolio returns for all securities

including financial institutions we notice that size factor have no impact on return of any

portfolios. market factor has impact on return because its p- value is 0.146 greater than 0.05 for

SL portfolio and value factor has insignificant impact on return as it has p- value that is lower

Page | 26


than 0.05.for SM portfolio both market factor and value factor have insignificant impact on

return as their p-value are ˂ 0.05. In SH and BL portfolios only market factor has impact on

return but it is insignificant as the p- value are lower than 0.05. As value factor has significant p-

value in BM portfolio, it has significant impact on return .Lastly only market factor has p-value

that is greater than 0.05 in BH portfolio indicating its significant impact on return.

7.2.2. Value weighted portfolio without financial institutions

In this portfolio we see that the average mean return for the large size companies is lower than

that of small size companies. The average mean return of large size companies is 0.031259

which is lower than that of 0.033121 of small size companies. This result is quite consistent with

our previous result and also with the tested model. In case of value effect consideration the

market is in consistent with three factor model because here growth companies are now

outperforming value companies.

Table 12: mean return and standard deviation for six portfolio without financial institutions

Table 13 summarizes that all factors have negative mean return except SMB that is small size

companies are outperforming big size companies. The negative mean return for HML and market

factor imply that growth companies are performing well and market return are lower than risk

free rate respectively that are inconsistent with the Fama-French Three factor model.

Mean Std.devSMB 0.0018617 0.0925323HML -0.0228871 0.0630206

Rm-Rf -0.2850045 3.990607

Page | 27

Portfolio Mean Std.

SL 0.0407081 0.1104031

SM 0.0361792 0.1214756

SH 0.0224759 0.1014727

BL 0.0423016 0.074107

BM 0.0367166 0.0838506

BH 0.0147598 0.0904637


Table13: Mean return and standard deviation of size and value factor


SMB 0.7687161 0HML -0.37318 0.001_cons 0.0298906 0

SM Rm-Rf -0.0030177 0.137 0.3815SMB 0.7259596 0HML 0.3245001 0.014_cons 0.0413944 0

SH Rm-Rf -0.0030606 0.029 0.5834SMB 0.593247 0HML 0.6976141 0_cons 0.0364655 0

BL Rm-Rf -0.0027499 0.038 0.2938SMB -0.3601261 0HML -0.2384335 0.006_cons 0.0367313 0

BM Rm-Rf -0.0036391 0.024 0.1888SMB -0.3672943 0HML 0.1965953 0.058_cons 0.0408627 0

BH Rm-Rf -0.0026557 0.112 0.2454SMB -0.1846569 0.013HML 0.6907723 0_cons 0.0301564 0

Table 14: regression analysis for value weighted portfolios (without fin. institutions)

Interpretation:

From value weighted portfolio without financial institutions by regression analysis we see that

only market factor has significant impact on return in SL, SM and BH portfolios as in this three

portfolios the market factor has p-value greater than 0.05.in SH and BL portfolios only market

factor has insignificant impact on return as it has lower p-value (˂0.05) whereas others two

factors have no impact on return. Finally we see in BM portfolio the value factor has only

Page | 28


significant impact on return as it has significant p-value (˃0.05) whereas market factor has

insignificant impact on return since it has lower p-value (˂0.05).

7.2.3. Portfolio index for value weight

Now if we look at the value weighted return index for all listed companies without financial

institutions, we see that growth and large size firms have higher return than that of value firms

and small size firms. This result is consistent with our previous result but inconsistent with the

three factor model (TFM).

growth stock

value stock


large size0

0.01

0.02

0.03

0.04

0.05

Mea

n re

turn

Figure 04: value weighted portfolio index with financial institutions

The chart for value weighted return index for all companies excluding financial institutions also

shows the same result that value firms that have higher net asset value compared to market value

underperform. Large size companies outperform that is these results threaten the three factor

model to the Bangladeshi stock market.

growth stock

value stock


large size0

0.01

0.02

0.03

0.04

Mea

n re

turn

Page | 29


Figure 05: value weighted portfolio index without financial institutions

8. Conclusions In this report I have investigated the robustness of the Fama and French Three-Factor-Model in

the Dhaka stock market for the period January 2002 – December 2013. I find that over the period

there is a negative market premium that is market return is lower than investors mostly expected

risk free return. The return for large size companies are higher than that of small size companies

and it violates the three factor model where it is shown that small size companies outperform

large size companies . Besides I see that growth companies have the higher return than that of

value size companies which also violates the Fama French three factor models where it is stated

that value companies get more return than that of growth companies. But I see the same result

from the regression analysis that size factor and value factor have no significant impact on result

but very interestingly I see that market factor can explain the return significantly over the last

thirteen years .So I want to say that Fama-French three factor model is not applicable in our

Bangladeshi stock market rather CAPM model can be applied in our stock market.

Page | 30


9. References 1) Ajili, Souad, 2005, The Capital Asset Pricing Model and the Three Factor Model of

Fama and French Revisited in the Case of France, Working Paper.

2) Banz, R.W., (1981), “The Relationship between Return and Market Value of Common Stocks,”

3) Barber, B.M., and Lyon, J. D. (1997) Firm size, book-to-market ratio, and security

returns: A holdout sample of financial firms, Journal of Finance, 52: p.875-883

4) Basu, S. (1977) Investment Performance of Common Stocks in Relation to Their Price -

Earnings Ratios: A Test of the Efficient Market Hypothesis, Journal of Finance 12:3, p.

129-156

5) Bhandari, L.C. (1988) Debt/Equity Ratio and Expected Common Stock Returns:

Empirical Evidence, Journal of Finance 43:2, p. 507-528

6) Bundoo, Sunil K., 2006, An Augmented Fama and French Three-Factor Model: New

evidence from an Emerging Stock Market, Working Paper.

7) Chan, K.C., Y. Hamao, and J. Lakonishok. 1991. Fundamentals and stock returns in

Japan. Journal of Finance 46: 1739-1764.

8) Connor, G and S. Sehgal. 2001. Tests of the Fama and French Model in India.

9) Daniel, Kent, and Sheridan Titman, 1997, “Evidence on the Characteristics of Cross Sectional variation

in stock returns, “Journal of Finance, Vol 52, pp .1-33.

10) Davis, J.L., Fama, E.F. & French, K.F. (2000), “Characteristics, covariance and average returns: 1929 to

1997,” Journal of Finance, vol. 55, No. 1, pp. 389–406.

11) Drew, M. E. and Veeraragavan, M., (2003), “Beta, Firm Size, Book-to-Market Equity and Stock

Returns: Further Evidence from Emerging Markets,” Journal of the Asian Pacific Economy, Vol.

8, No. 3, pp. 354

12) Faff, R.W., (2001), “An Examination of Fama and French Three Factor Model Using Commercially

Available Factors,” Australian Journal of Management, Vol.26. No.1, June 2001, pp.1-17.

Page | 31


13) Faff, Robert, (2004)" a simple test of the Fama and French model using daily data: Australian evidence",

applied financial economics, Vol 14, pp 83-92.

14) Fama, E.F., and French K.R. (1995) Size and Book to Market Factors in Earnings and

Returns, Journal of Finance, 50, p.131-155

15) Fama, E.F., and French K.R. (1996) Multifactor Explanation of Asset Pricing

Anomalies, Journal of Finance, 51, p.55-84

16) Fama, E.F., and French K.R. (1998) Value versus Growth: The International Evidence,

Journal of Finance, 53, 1975-1999

17) Fama, E.F., and French K.R. (2004) The Capital Asset Pricing Model: Theory and

Evidence, Journal of Economic Perspectives 18, p.25-40

18) Fama, E.F., and French, K.R., (1992), "The Cross-Section of Expected Stock Returns", The Journal

of Finance , Vol. 47, No. 2, pp. 427-465.

19) Gaunt, Clive, 2004, Size and Book to Market Effects and The Fama French Three

Factor Asset Pricing Model: Evidence from the Australian stock market, Accounting

and Finance 44, 27-44

20) Kothari, S.P., Shanken, J., and Sloan, R.G. (1995) Another Look at the Cross-Section of

Expected Stock Returns, Journal of Finance, 50, p.185-224

21) Lakonishok, J., Shleifer, A., and Vishny, R.W. (1994) Contrarian Investment,

Extrapolation and Risk, Journal of Finance, 49, p.1541-1578

22) Malin. M and Veeraraghavan. Madhu, (2004)" On the Robustness of the Fama and French Multifactor

Model: Evidence from France, Germany, and the United Kingdom,” International Journal of

Business and Economics, 2004, Vol. 3, No. 2, pp. 155-176.

23) Nartea, G.V. and H. Djajadikerta, 2005, Size and Book to Market Effects and the Fama-

French Three-Factor Model: Evidence from New Zealand, Proceedings of the UM-FBA

Asian Business Conference, Kuala Lumpur, Malaysia, pp. 510-521.

24) Petkova. Ralitsa, (2006), “Do the Fama–French Factors Proxy for Innovations in Predictive

Variables?" The Journal of Finance. Vol.Lxi, No.2. April 2006, pp. 581- 612.

25) Rahman, N.Baten, A.Alam, A.” An empirical of Capital Asset Pricing Model in Bangladesh",

Journal of Applied Sciences Vol. 6 (3), pp 662-667, 2006.

Page | 32


Page | 33

Report on Fama French Three Factor Model

Documents

Transcript of Report on Fama French Three Factor Model