The Impact of Foreign Ownership on Stock Return Volatility of the Financial, Industrial, Holding Firms, Property, Service, Mining & Oil Industry for the Years 2008-2012

A Thesis Draft Presented tothe Financial Management Department,Ramon V. Del Rosario College of BusinessDe La Salle University

In Partial Fulfilment ofTHSMAFIBachelor of Science Management of Financial Institutions1st Trimester, AY:2014-2015

Submitted by:Barroso, Frances Angelie T.Co, John Kevin O.Icaranom, Danica G.Jaranilla, Jan Keith H.

Table of Contents

1. Introduction 1.1 Background of the Problem4 1.2 Statement of the Problem 6 1.3 Objectives of the Study 71.4 Hypothesis71.5 Significance of the Study 81.6 Scope and Limitation 92. Review of Related Literature2.1 Financial Liberalization in Emerging Markets102.1.1 Philippine Laws on Large Foreign Ownership102.2 Corporate Governance, Corporate Operational Efficiency, and Firm Performance172.3 Foreign Ownership, Stock Return Volatility, and Firm Performance192.4 Other Sources of Stock Return Volatility 212.5 Research Gap232.6 Literature Map253. Framework3.1 Theoretical Framework 26 3.1.1 Efficiency 22 3.1.2 Technical Efficiency27 3.1.3 Technology Spillover Effect 283.1.4 Efficient Market Hypothesis28 24 3.3 Conceptual Framework 293.4 Operational Framework 314. Research Methodology 4.1 Research Design 414.2 Data Description and Collection Method 424.3 Method of Data Analysis 4.3.1 Preliminary Test 46 4.3.2 Test for Corporate Operational Efficiency 4.3.2.1 Data Envelopment Analysis46 4.3.2.2 Vector Auto-Regression Model484.3.3 Test for Firm Performance 4.3.3.1 Regression484.3.4 Test for Stock Return Volatility 4.3.4.1 Regression494.4 Methodological Limitations 51

CHAPTER 1INTRODUCTION1.1 Background of the StudyGlobalization became a buzzword in the 21st century. In order to participate in the global competitiveness, and perceiving the possible advancement that this may bring to the engaging nations, Philippines acquiesced with the World Trade Organization in 1995 and entered the global economic arena. However, despite its great anticipation in its enlistment, the country was far behind the economic performance of its neighboring Southeast Asian nations. Penetrating the global realm without a strengthened domestic political economy, Philippines gravely failed giving it the epithet Sick Man of Asia (Banlaoi, 2004). However, with the dynamic growth of the Philippine economy in the more recent years, it has emerged as a bright spot among emerging markets in the world. For the fourth quarter of 2013, Philippines capped its strongest two years of growth since the 1950s. According to a poll conducted by the Philippine Statistics Authority, Gross Domestic Product rose to 7.2% in 2013 after gaining 6.8% in 2012. From being the Sick Man of Asia, the country is slowly becoming a rising tiger with its robust domestic spending, sound fiscal management, and resilient remittance inflows (Yap, et. al, 2014).

The Philippines is already recognized by the leading credit rating agencies such as Fitch Ratings, Standard & Poors and Moodys, awarding it with its first investment grade in 2013 (Lucas, 2013). Although its credit rating of BBB- is the lowest in the investment grade spectrum, it still depicts an immense potential, given that the first credit rating awarded did not fall on the speculative grade. This suggests that the countrys debt has a low risk of default. Being granted an investment grade signals the attainment of international respect and recognition that it is a solvent country that has the capacity to repay its debt.

The emerging market index launched by Morgan Stanley Capital International (MSCI) discloses that the Philippines is the worlds best performer out of the 45 emerging and developed markets being tracked. Among the 45 emerging and developed markets are: India, Indonesia, Malaysia, Sri Lanka, Taiwan, and Thailand to name a few (Mellor, 2013). The countrys ascent to investment grade status is ratification of the countrys emerging status and of the significant increase in overseas funds coming in from foreign investors eager to capitalize on the opportunity. This will result to a larger percentage of foreign ownership in the economy. With this, the countrys stock market will be further exposed to foreign investors in order for it to go with the flow of stock market liberalization.

However, the stock market cannot be completely liberated because of the 1991 Foreign Investment Act. The act cites foreign investment restrictions known as the Foreign Investment Negative List. This defines the foreign investments that are limited or restricted by the Constitution of the Philippines and other specific laws. The list is divided into two, Negative List A and Negative List B. Under these lists, the maximum percentage of foreign ownership is about 60% of the equity. However, it goes as low as restricting the company to a zero for foreign investors.

Nonetheless, it is still quite debatable whether the stock market should be completely liberated, with the controversial stands on what foreign investors bring to the market and to the economy.Foreign investors allegedly come and go quickly, making foreign capital flows a source of domestic stock market volatility and even financial crises (Chen et. al, 2006). The 1997 Asian Financial Crisis for instance, although it cannot be blamed on foreign investors alone, they were criticized for playing a big hand in the crisis. In 1996, while Koreans invested $2.4 billion in foreign equity and debt securities, foreigners invested $16.8 billion in Koreas securities. Foreign investors held more of Koreas securities than the Koreans themselves, not considering that these investors can easily come and go. In October 1997, for example, as trouble developed in the Hong Kong and other stock markets, foreign investors began to flee the Korean equity markets. Over the weekend of October 25 following the fall in the Hong Kong stock market, foreign investors sold $22 million worth of Korean stocks. This started a rush out of Korean securities that sent the composite index of stock values on the Seoul exchange to a ten-year low of 450.6 on November 24, 1997, down by 30% for the year (Nanto, 1998). The severity of capital flight out of crisis countries amplifies financial asset volatility and heightens the crisis. In addition to this, when domestic firms become highly accessible to foreign investors, the local firms stock trading also becomes vulnerable to world market risk. (Bae et. al, 2004). Domestic firms can no longer just consider its own market, but has to take into consideration the economic implications and risks brought by its foreign investors.

On the contrary, other studies have shown that foreign ownership produces a stabilization effect on the volatility of stock returns. The heterogeneity among foreign investors has been recognized as beneficial in emerging stock markets for they do not only supply monetary aid but also technological resources, business relations, development of human capital, and demand transparency and higher accountability of management. These result to the significant positive effect of foreign ownership to corporate operational efficiency, which then triggers higher corporate performance. In return, higher corporate performance leads to the stabilization of the volatility of stock returns. The stabilizing effect can be best defined as the minimization of the volatility of stock returns at the median level due to the percentage of foreign ownership. The stabilizing effect of foreign investors documents a significantly negative relationship between foreign ownership and stock return volatility. In addition to the stabilization effect, foreign investors finance economic growth, further develops domestic stock markets, and reduces cost of capital through risk sharing between domestic and foreign investors (Li et. al, 2010).

However, with the percentage restrictions in foreign ownership in the Philippines, the country may not be able to benefit from this stabilizing effect. Philippines, Ethiopia, and Thailand are amongst the worlds most restricted economies. Some of the sectors for the countries mentioned completely restrict the participation of foreign investors. This raises the question on whether Philippine industries and firms would yield greater performance and a more stable stock market with foreign ownership. .

1.2 Statement of the ProblemThe study will focus on the impact of the presence of foreign ownership to stock return volatility among domestic listed firms in the Financial, Industrial, Holding Firms, Property, Service, and lastly the Mining & Oil Industry under the Philippine Stock Exchange (PSE). Particularly it would like to address the following questions:a) Does foreign ownership stabilize stock return volatility?b) If there is a stabilization effect, which among the six sectors under the PSE is most and least stabilized by foreign ownership?

1.3 Objectives

Considering the percentage of foreign ownership in the Financial, Industrial, Holding Firms, Property & Service, and lastly the Mining & Oil Industry under the PSE, the researchers intend:a. To determine whether foreign ownership has an impact on the stock return volatility of firms listed under the Philippines Stock Exchangeb. To determine whether foreign ownership stabilizes the stock return volatility of firms listed under the Philippine Stock Exchangec. To determine which among the six sectors is most and least affected by the stabilization effect of foreign ownership.

1.4 Statement of Hypothesis

H0: Foreign ownership has no impact on stock return volatility.H1: Foreign ownership has an impact on stock return volatility.H0: There is no stabilization effect on the volatility of stock returns due to foreign ownership.H1: There is a stabilization effect on the volatility of stock returns due to foreign ownership.

1.5 Significance of the StudyAs empirical evidences regarding the relationship between foreign ownership and stock return volatility are mixed and contrasting, it is important to measure the potential impact of the former to the latter in financial liberalization processes and decisions by policymakers. The main purpose of the study is to prove if the presence of foreign ownership has a significant impact on the volatility of stock returns under PSE. This will be further broken down between the six industries under the PSE. These industries are Financial, Industrial, Holding Firms, Property & Service, and lastly the Mining & Oil Industry. By doing so, we can magnify to which industry does foreign ownership produce the greatest stabilizing effect. Specifically, the studys results are intended to be beneficial for the following: (1) domestic firms this study may support their decision making on whether foreign ownership limit must be more restricted or loosened, (2) economic policymakers this study may aid their research in identifying the rules and regulations that must be implemented with respect to foreign investors, and (3) future researchers this study may be used as a comparison to their future studies regarding the same topic.

1.6 Scope and Limitations of the Study

The study will be limited to the determination of the impact of the presence of foreign ownership to stock return volatility among domestic listed firms in the Financial, Industrial, Holding Firms, Property & Service, and lastly the Mining & Oil Industry under PSE for the years 2008 until 2012 only. Results will be presented in an industry basis due to the fact that they may behave in different ways depending on their industry. Moreover, the law has imposed sector-specific regulations which may include certain restrictions. The firms to be included in the study must be listed under PSE since January 2008 and must still be actively trading in the present. On the possibility that data of particular firms will not be available on any of the sources (Bloomberg, PSE, Osiris) to be utilized, the following firms will no longer be included in the study. Also, only the stock that was listed first under PSE will be included for firms that are trading under two stock symbols (e.g. FYN, FYNB). Given that this study involves stocks, there could be significant factors or other variables, which are not accounted for in the model. The volatility is to be determined through the returns of the stocks published in Bloomberg. Any shareholder whose country listing in Bloomberg is not Philippines is considered as a foreign shareholder in this study.

CHAPTER 2REVIEW OF RELATED LITERATURE

2.1 Financial Liberalization in Emerging Markets

Financial liberalization in emerging markets has been continuously gaining attention as the International Monetary Fund and World Bank have been encouraging developing countries in opening its financial market for purposes of achieving economic growth and financial stability (Chen & Lu, 2007)as their study found that such move is beneficial to these types of countries. As a definition of Li et. al (2010), equity market liberalization refers to the policy wherein the government of a country allows foreign investors to purchase shares in the financial equity market of that domestic country. Moreover, domestic investors are given the right to transact in foreign shares. This allows domestic economic growth to be financed by foreign investors due to their accessibility (Aimipichaimongkol & Padungsaksawasdi, 2013). This is further supported by Levin and Zervos (1998) as they find that there is a positive significant relationship between stock market openings and long run economic growth. Moreover, they have concluded that it results to an improvement in market efficiency, global diversification, internationally risk-sharing and steady-state welfare gains. As emerging markets become globally influenced (Bae and Chan, 2001), the development of domestic equity markets are hastened by (Kim & Singal, 2000).

However, such benefits remain a concern as it is a characteristic of an emerging market to have a high volatility as compared to developed markets (Wang, 2007). This researcher also states that high volatility entails increasing cost of capital, deterring investments, and impeding long-run stock market development. Similar to Levine and Zervos (1998) findings, volatility has surged after opening the market in 16 countries. If a country becomes an integrated market from being a segmented market, prices tend to rise while expected returns decrease (Bekaert and Harvey, 2000). However, the reaction of the market may still depend on the policies implemented by a domestic market (Nyangoro, 2013)

2.2 Philippine Stock Exchange

Similar to the studies of Hammoudeh et. al (2010) on the US Sectors, they find that stock return volatility in different sector varies. In the Philippine setting, according to the listing in Philippine Stock Exchange, we have six industries in total: Financial, Industrial, Holdings, Mining & Oil, Property, and Service Industry. Although the 60-40 percent local-foreign ownership limit has been set to be uniformly adopted by the publicly listed companies, certain firms have stated in their most recent (September 2013) public ownership reports that they set no limit for foreign ownerships. The firms listed under the PSE have classified common share into two: Class A and Class B. The former are stocks that can be exclusively traded by Filipino investors, while the latter are stocks that can be bought or sold by both Filipino and foreign investors (PSE Academy, 2011). These ordinary shares have only been divided in order to have a better monitor of ownership levels of domestic and foreign investors; therefore, the same amounts of dividends are received by these classes. These types of shares, as defined in the website, are often purchased for profits and ownership control and management. Generally, they may be able to exercise their control through voting rights. 2.3 Roles of Foreign Investors to Domestic Firms

Several researchers have already conducted studies with respect to the relationship between foreign ownership and domestic stock return volatility. They have mostly focused on emerging markets either individually or in aggregate. Wang (2006) has stated that, as compared to developed markets, there is higher stock market volatility in emerging markets. With different sets of data, some result to a negative relationship between the said variables while some conclude otherwise. As evidenced in studies of emerging markets, capital market liberalizations results to reduction in volatilities of individual stock returns. This is confirmed and implied by Umutlu et. al (2009) where results have shown that the increasing degree of financial liberalization has a decreasing impact on aggregated total volatility. Such implication is supported by the view that volatility is reduced as the accuracy of public information enhances due to the said liberalization.

Despite controlling for potential endogeneity and taking into account other significant variables, consistent results were seen wherein having a large foreign ownership drives a reduction in volatility (Li et. al, 2010). Such finding is also true for the firms listed in the stock exchange of Thailand which were entirely focused on the industrial sector as Aimpichaimongkol & Padungsaksawasdi (2013) take into account the heterogeneity among foreign investors. Existing evidence was reinforced from the study that large foreign investors play a stabilizing role in equity markets.

First, this could be supported by an interpretation by Wang (2007) and Li et. al (2010) that the power of having a monitoring role is used by some large foreign shareholders. Since emerging markets are generally characterized to have information asymmetry, the entrance of foreign investors becomes favorable to such firms (Wang, 2007). Greater transparencies are demanded and less risk are taken by these investors (Li et. al, 2010).

Second, as the investor base increases due to foreign ownership, it results to higher return and greater risk sharing (Merton, 1987) which leads to volatility reduction (Wang, 2007). A possible specific example would be having less reliance on debt financing (may induce stock return volatility) as there is more support from foreign investors (Mitton, 2006). In addition, due to accurate forecasts by foreign analysts (Bacmann and Bolliger, 2001), there may be greater investor confidence on a stock as reported by Huang and Shiu (2009).

Finally, it is argued that foreigners who are capturing a proportion in the shares of a firm imply that their purpose for such investment do not solely direct to providing monetary capital but also resources, technology, and training of human capital. Similar to Stulz (2005) discussion, this could be attributed to an improvement in corporate governance as foreign shareholders offer tools and incentives in doing so. This is further supported and emphasized by Mitton (2006) and Lee and Huang (2013) that when domestic firms become accessible to foreign investors, profitability as represented by operating results tend to improve as well. Moreover, according to Ferreira and Matos (2008), there is a positive relationship between performance measures and shareholdings by foreign institutional investors.

Many of the sources we have gathered stated that according to Vishny (1997) corporate governance refers to the way in which suppliers of finance assure themselves of investment. Firms with relatively strong corporate governance tend to have a significantly lower volatility (Li et. al, 2010). Foreign investors make certain arrangements in the company where they invested in to ensure the companys growth to gain returns on their investments. Due to the changes in behavior in arrangements and operation markets, corporate governance has been playing a big role in an investors investments.According to Bebchuk and Weisbac (2010), when investors become shareholders of a company, an investor may either implement their knowledge on financial basics or gather information about the company. As an example, according to Aggarwal et als (2011) study, there is greater corporate governance when CEOs are terminated due to a poor performance. Moreover, foreign investors can make changes in the companys operation by increasing the operational efficiency of the firm the foreign investor invested in. As described by Lee and Huang (2013), due to monitoring effectiveness and disciplinary roles, agency problems are resolved between investors and managers. This may specifically include playing a disciplinary role which may affect corporate and investment decision making (Choi et. al, 2012). This may affect the operational efficiency of the firm. As operational efficiency increases, performance is positively triggered (Lee and Huang, 2013). Companies with foreign ownership and greater operational efficiency have high return on assets (ROA), which translates to higher firm performance (Lee and Huang, 2013). Another study that focused on operational performance of Japanese firms and their corporate governance states that corporate governance is linked performance of a firm. Sueyoshi et. al (2010) argues that using an effective governance system, [Japanese manufacturing firms] are directed toward improving their performance and maximizing the corporate value of their firms." Similar to the 1997 Asian financial crisis, capital flows from foreign ownership are often blamed as they come and go which leads to volatility (Chen et. al, 2007). It is an inherent matter in the opening of the market to foreign investors brought about by financial liberalization, the incidence of deregulation leads to an increase in the volatility levels of firms (Comin & Philippon, 2005). The previous statement is said to be consistent with findings that an increase in the number of foreign investor results to greater volatility in the market as it is evidenced by several studies.

First, a different study by Bailey et. al (2008) made an analysis in foreign investors focusing on their potential speculative characteristics when participating in the stock market. The participation of these foreign speculators was found to have used foreign securities for speculation. Their speculation is referred to as short-term capital movements which are reversible (Nyangoro, 2013). It implies that they tend to leave as fast as they come in an economy (Bekaert et al., 2012). Thus, this leads to a drastic impact on the economy subsequently affecting companies share value as the productivity of its capital stock is lowered (Gazioglu, 2008); in turn, the aggregate stability of the stock market (Bekaert et al., 2012). Kim and Wei (1999) also defines this as a kind of positive feedback trading wherein foreign investors sell when prices have decreased and buy when increased. According to Bailey, et. al (2008), holding foreign equity makes a diversification benefit as their stock returns among different countries appear to have a low correlation. This is similar with Conover et al. (2002) and Allen et. al (2011) wherein they find that foreign investors are able to hedge against risk together with getting higher returns as correlation between emerging markets and developed markets are not perfectly correlated.

Second, as domestic firms become more integrated into the world economy (Li and Wei, 2006); thus, having stock prices of such firms are affected through international market information. As argued by (Ross S. , 1989), market volatility is related to the information flows which implies that information from one stock market can be incorporated in another stock market; thus affecting movement of prices and subsequently, its volatility. This results to domestic investors hedging against international stock market risk. According to Li and Weis (2006) study on Chinas stock market, firms which have issued shares for foreign ownership (B-shares and/or H-shares tend to have a larger stock return volatility ) as compared to those with only A-shares (shares only traded domestically). Moreover, as foreign investors drive up domestic prices though their demands while assuming superior information, later on, prices are forced to be corrected. Immediately after such changes, these investors tend to move out of the market (Nyangoro, 2013).

These claims can be further emphasized through the study of the relationship between investability (measures how accessible the stocks are to foreign investor) and return volatility in emerging equity markets by Bae and Chan (2001). It is similarly argued by Tesar and Werner (1995) that there is higher turn-over rate on shares held by foreigners or non-residents as compared to the domestic market. According to these researchers, there is more volatility in highly investable stocks than non-investable stock even after controlling certain variables (country, industry, size, and turnover).

2.4 Other Sources of Stock Return Volatility

It could be said that it is undisputable that there are several sources of stock return volatility in the market. The movement of stocks prices, which in effect directs to the returns, can also be attributed to the ownership structure of firms. As mentioned in the preceding statements, there are evidences of the significance of foreign ownership. This entails that domestic ownership may affect the value of its own stocks. Although Li et. al (2010) has only accounted large domestic shareholders who may defined to be controlling shareholders, their study states that such shareholders may avoid active stock market trading since they are long-term investors; thus, free-float shares may reduce which leads to lower stock return volatility. Sarkar and Sarkar (2000 has also provided evidence that large shareholders has the role to monitor company value. Such statement could imply that domestic shareholders could be accountable to the changes of their stock prices through their influences on their companys performance. In return, firms performance could be reflected on the market values of their shares. Local controlling shareholders, according to Sun and Tong (2003), tend to incline into making sound business decisions because such investors have the resources, mechanisms and business knowledge that are necessary to ensure effective monitoring management. Consequently, domestic ownership concentration may result to high firm volatility due to potential expropriation (Bae, et. al, 2000). Moreover, there is lack of credibility as domestic institution rarely engage in firm research (Huang and Shiu, 2009) which could be an implication that such domestic investors may trigger volatility of publicly listed firms.

Aside from the ownership structure and identities of shareholders, Li, et. al (2010) has mentioned that firms with great market capitalizations follows lower volatility on the movement of its stocks. This is confirmed in Bae & Chan (2001)s research where it has been indicated in their results that there is a significant and negative relationship between firm size and return volatility implying that larger firms are less volatile as compared to smaller firms; thus, consistent with the small company effect (Zou & Adams, 2008). Firms with low market capitalization tend to have greater impacts of shocks in volatility as Cheung and Ng (1992) have stated. Thus, in such situation, small firms are more susceptible to uncertainty in stock prices. However, this is contradicted by Nyangoro (2013) as it is stated in his study that the higher proportion of market capitalization comes from foreign participation when domestic stock market are opened for them.

Several studies (Li, et. al (2010), Wei and Zhang (2006), Aimpichaimongkol and Padungsaksawasdi (2013)) have included leverage as one of the important determinants of volatility. Using the ratio of total liabilities to total assets, results have shown that stock returns are more volatile in firms where there is high leverage. Zou and Adams (2008)s results also suggest that there is lower equity risk in companies having low-leverage due to a low debt financing. A concept called Leverage Effect stated by Black (1976) explained that leverage can induce future stock volatility to vary inversely with the stock price: a fall in a firm's stock value relative to the market value of its debt causes a rise in its debt-equity ratio and increases its stock volatility. Furthermore, as studied by Bhatti et. al (2010) on 8 industries in Pakistan, a high level of leverage leads to a high systematic risk, this, in turn, results to higher volatility of stock prices and its returns.

The lags of volatility in the market are also considered to be factors on the changes of stock return volatility as is known that the said variable is auto-correlated with the latter (Li, et. al, 2010). As Lo and MacKinlay (1988) exploits the return variances scale, they find that there is positive serial correlation in weekly returns due to increasing variances as holding period increase.

High volatility is also generated through an active traded trading turnover (Li, et. al, 2010). This is supported by Wang and Huangs (2012) findings that when a private information provokes jumps (sudden changes in price), there is greater positive relationship between turnover and stock return volatility as this type of information needs large trading volume to reveal itself. On the other hand, Giot et al. (2010) and Wang and Huang (2012) finds that there is a negative relationship between trading volume (which is a component of turnover) and movements of stock prices. Andersen et. al (2007) believes that this could be due to the public information (such as macroeconomic information) that lies behind such stock. This could be supported by Wang and Huangs (2012) example that there is a quick and sharp price change without much trade when traders have the same view on the stock valuation. Moreover, when the same information consistently spreads in the market, there is lower volatility as investors may just buy (or sell) the stock in which price movements will be in the same direction. The same researchers have also said than another reason would be investors who might have temporarily stopped trading in the middle of the day to revaluate their portfolios. However, Bae et. al (2004) finds that the return volatility of stocks which are open to foreign investors is not completely due to trading activity or turnover.

2.5 Research Gap

As an emerging country, foreign investors become attracted to the Philippine stock market leading to their acquisition of shares of domestic firms. Aside from theoretical and empirical evidences that such stock market liberalization lead to economic growth (Li, et.al, 2010), it is important to note that there could be a bottom-to-top effect wherein these foreign investors directly impact the stock and firm-level performance first before they aggregately affect the countrys economy. Li, et. al (2010) has also stated that in the process of liberalization, the impact of foreign investment on domestic stock return volatility is a primary concern. As previously mentioned in the literatures preceding this section, there have been a number of confirmations that foreign ownership leads to reduction in volatility of stock returns as it makes a stabilization effect while other studies suggest otherwise.

Many have already conducted studies relating the relationship between foreign ownership and stock return volatility. However, they have either estimated analysed certain specific emerging countries individually or aggregately (which includes the Philippines. In line with this, this paper will show an examination of the significance and relationship of such investments in the stock return volatilities while taking into account the firms industry sectors in the Philippines.

2.6 Literature MapFinancial Liberalization(Aimipichaimongkol & Padungsaksawasdi, 2013); (Bae and Chan, 2001); (Chen & Lu, 2007); (Kim & Singal, 2000); (Levin and Zervos, 1998); (Nyangoro, 2013)Foreign Investors and Stock Return Volatility(Li et. al, 2007); (Umutlu et. al, 2009);(Wang, 2006); (Wang, 2007)Foreign Investors with Monitoring Role(Aimipichaimongkol & Padungsaksawasdi, 2013); (Bacmann and Bolliger, 2001); (Ferreira and Matos, 2008); (Huang and Shiu, 2009); (Lee and Huang, 2013); (Li et. al, 2007); (Merton, 1987); (Mitton, 2006); (Stulz, 2005)Foreign Investors as Speculators(Allen et. al, 2011); (Bailey et. al, 2008); (Bae and Chan, 2001); (Bekaert et. al, 2012); (Chen et. al, 2007); (Comin & Philippon, 2005); (Conover et. al, 2012); (Gazioglu, 2008); (Kim and Wei, 1999); (Li and Wei, 2006); (Nyangoro, 2013); (Ross, 1989); (Tesar and Werner, 1995)

CHAPTER 3FRAMEWORK3.1 Theoretical Framework

3.1.1 Efficient Market Hypothesis

The efficient market hypothesis (EMH) states that a market is efficient if security prices immediately reflect the available data as developed by Paul A. Samuelson and Eugene F. Fama in the 1960s. This entails that price changes are random and unpredictable in a strongly efficient market as all information and expectations of all market participants (Lo, The New Palgrave: A Dictionary of Economics, 2007) have been already incorporated. According to Fama (1965), such markets is not an accident of nature but a result of the attempt of market participants to profit given their information. In a world where there is no cost of trading, profit opportunities may quickly eliminate through the information incorporated as this occurs instantaneously. It is one of the most common fundamentals of financial theories.

There are three categories of the EMH; the weak, semi strong and strong EMH. The weak form of EMH suggests that stock prices can be determined by examining trading data. In the weak form, data is generally readily available and if the weak form holds, stock prices should be composed of three components. These components are previous stock prices, expected return on stock and a random error term. There is a random error term for there is still unexpected information released during the period. This form of efficiency suggests that patterns in past data cannot be used to predict prices. This emerged as a response to empirical evidences that there exists a random walk effect on stock market prices (Hayes, 2012) wherein investors cannot make use of the technical analysis strategy which refers to the use of geometric patterns in price and volume charts to forecast future price movements of a security (Lo, 2007).

The semistrong form of EMH asserts that stock price reflects all publicly available information of the firm. The information needed is information such as annual reports and investment advisory data that are readily available for the public. In this type of efficiency, prices reflect fundamental value (Hayes, 2012) - which may include the present value of the future cash flows of the share. This means that the information reflected on the prices are based on rational expectations. Such statements are against the strategy of fundamental analysis where they primarily expect to get a return through their observation on market interest rates and/or yield of assets (Hayes, 2012) which they may view as not being reflected on the prices yet.

The last category is the strong form and it holds that current prices reflect all true information, which is only known by company insiders. For a strong-form efficiency to hold, the weak and the semi-strong should have to hold first. In summary, the efficiency market hypothesis holds that the market quickly responds to information on both individual and the economy.

The concept of behavioral finance sets a critique on the Efficient Market Hypothesis. It state that smart money (i.e. investors with rational expectation) offsets noise traders (i.e. investors who trade on the basis of non-news or pricing models with no rational foundation) (Hayes, 2012) as they make irrational trading. Investors may have behaviors of under- (conservatism) and over-reaction (representativeness) to news. (Shleifer A. , 2000). When investors are slow in changing or revising their expectations as they await the news to confirmed, they adopt the concept of conservatism. Event studies have shown that this leads to excess returns for a certain period (i.e. 60 days) after the announcement. On the other hand, when investors categorize stocks either under winners or losers as they may have good or bad return, respectively, this implies representativeness. This is referred as over-reaction since their views may result to being much deviated from the fair or rational market value (Lo, 2007) or what EMH would warrant (Shleifer, 2000). These two concepts may be summarized as positive feedback trading.

Additionally, Grossman and Stiglitz (1980) argue that a perfectly efficient market is impossible since such hypothesis entail that there will be no profits in gathering information; thus, leading to a collapse as there would be less reason to trade. Given these still existing arguments, the current state of the EMH is seen to be unresolved as each side of the debate are continuously supported by other theoretical models and statistical analysis (Lo, 2007).

3.1.2 Agency TheoryAs stated by Eisenhardt (1989), economists have been exploring the risk sharing among individuals or groups. This particularly relates to their different risk preferences agency theory broadens this risk-sharing literature. The theory of agency has always been controversial especially when applied in practicality. In simple terms, the problem arises between two (or more) parties when one, designated as the agent (i.e. managers), acts for, on behalf of, or as representative for the other, designated the principal (i.e. shareholders), in a particular domain of decision problems (Ross S. , 1973). It should be noted, however, that there may also be differences among the principals or shareholders wherein some may have different strategies in monitoring or better knowledge of the market which may induce greater firm performance (Kumar, 2005). The concern of this theory is resolving the problem of risk sharing. In relation this, studies were conducted in identifying ownership structure device in reducing agency costs (separation of ownership and management). It is argued that large shareholders have the tool in collecting information and monitoring management which helps in reducing such agency costs (Shleifer & Vishny, 1986).

3.2 Conceptual Framework

In an emerging economy, stock market liberalization is a factor to be considered in policy decisions given that the attractiveness of the economy is slowly becoming evident to foreign investors. Stock market liberalization increases the exposure of domestic stock markets to foreign investors and benefits through the attraction of foreign capital for economic growth, development of local stock markets, and risk distribution, which reduces the cost of capital. Aside from cross-border capital flows, foreign ownerships are reported to institute a stabilizing role in emerging stock markets due to greater corporate efficiency and higher firm performance brought by the shareholders.

Li et. al (2010), argues that the stabilizing effect brought by foreign investors is beyond its risk sharing and monetary capital broadening. Foreign investors also offer technological resources, business relationships, access to new export markets, and human capital training. Their investments go beyond the monetary spectrum and translate into operational support for the firm. Due to operational support, foreign investors demand greater transparency and higher accountability of management. They now play a monitoring role, which results to greater corporate efficiency.

Due to corporate efficiency brought about by foreign shareholders, higher firm performance is obtained which triggers a stabilizing effect that impacts the volatility of stock returns. The stabilizing effect can be best defined as the minimization of the volatility of stock returns due to the percentage of foreign ownership. The stabilizing effect of foreign investors documents a significantly negative relationship between large foreign ownership and stock return volatility. It is able to minimize the fluctuations of stock returns because foreign shareholders invest in domestic stock markets for the long-term return. Aside from monetary capital, these foreign shareholders invest their resources such as technological advancement, business connections, and the further development of human capital. In return for the operational and financial resources, foreign shareholders demand as well greater transparency and higher accountability management, which entices firms to improving their corporate operational efficiency and leads to higher firm performance. These resources and the improvement of corporate efficiency and firm performance translate to operational support allowing firms to extinguish external risks. The existence of the stabilizing effect in the Philippine Stock Market may highlight the importance of recognizing heterogeneity among investors.

As the economy of emerging markets become more and more integrated in the world economy through the opening of the stock market, information become much more available. Opening the financial market tends to result to either further volatility or stabilization as the sensibility of volatility to news increases. The movement of the value of shares may depend on the strength of the information the participants may have and whether such information has already been incorporated or reflected on the market.

Foreign investors may adopt the positive feedback trading wherein they may buy or sell when their perspective on certain stock are either good or bad, respectively, depending on their returns. This may result to movements of stock prices (and their returns) beyond their rational prices. On the other hand, as it has been discussed in previous studies, foreign investors tend to move the prices initially as they make use of the information they have on a certain firm. Eventually, these may be finally incorporated on the stocks value; however, resulting to drastic changes surfacing as excess volatility. 3.3 Operational Framework

In this study, the models to be used in testing for the foreign ownerships impact on stock return volatility of local firms are presented below. Moreover, the variables to be used, which are deemed necessary to be included, as evidenced by previous researchers can be seen in the proceeding parts. = - + + +

where:, represents the stock return volatility of firm in industry represents foreign ownership (%): represents dummy variables of each sector represents all control variables represents the error term of firm in industry

FO denotes foreign ownership with foreign shareholders who each have a percentage of the domestic firms issued shares. Foreign investors or corporations holding such shares refer to those citizens of another country or firms registered and listed under the laws outside the Philippines.

This studys independent variable, stock return volatility, will be calculated using the formula below:

In the statistical context, the mean of the quarterly stock return volatility will be calculated using the daily stock return of each firm in the same quarter.

The independent variable, FO, and control variables which are denoted by include the following:

(1) Foreign Ownership (FO) which refers to the aggregate block shareholdings held by non-Filipino individual or corporations or those not established under the Philippine laws; calculated as follows:

(2) domestic ownership (DOM) which refers to the aggregate shareholdings held by local (established under the laws of the Philippines) corporations or individuals; calculated as follows:

(3) natural logarithms of quarter-end market capitalization (LnMKTCAP) of domestic firms

(4) leverage (LEV) of domestic firms; calculated as follows:

(5) lag of the stock volatility (srvlag) of domestic firms

(6) trading turnover (TO) of domestic firm shares; calculated as follows:

These are purposely categorized to be controlled due to empirical evidences that such variables significantly affect stock return volatility of firms.

VariablesA-priori ExpectationVariable Description

Independent VariableForeign Ownership(FO)(-)FO is to be measured using a percentage equivalent of the shares owned over the total outstanding shares. Firms with shareholdings of foreigners lowers stock return volatility of local firms by stabilizing such movements of stocks

Dummy Variables (Sector)Financial Sector(FIN)(+)A dummy variable representing firms in the financial sector; zero otherwise

Industrial Sector(IND)(+)A dummy variable representing firms in the industrial sector; zero otherwise

Holding Firms Sector(HOLD)(+)A dummy variable representing firms in the holding firms sector; zero otherwise

Service Sector(SER)(+)A dummy variable representing firms in the service sector; zero otherwise

Mining and Oil Sector(MIN)(+)A dummy variable representing firms in the mining and oil sector; zero otherwise

Property Sector(PRO)(+)A dummy variable representing firms in the property sector; zero otherwise

Control VariablesDomestic Ownership(DOM)(-)DOM is to be measured in percentage value using the formula in the preceding sections. With more shares held by domestic corporations and individuals , the movement of stock returns reduces as they seem to take part on the control of the firm

Natural logarithm of market capitalization(LnMKTCAP)(-)Market capitalizations of local firms will be under a logarithmic transformation. Firms with greater MKTCAP are expected to have lower stock return volatility.

Leverage(LEV)(+)As leverage of firm increases, the uncertainties of stock return rises as well which could be attributed to its high equity risk.

Lag of volatility(srvlag)(+)The existent autocorrelation indicated that the lags of volatility in the market positively induces stock return volatility

Trading turnover(TURNOVER)(+)Excessive trading results to further movements in the stock returns of local firms

CHAPTER 4METHODOLOGY4.1 Research DesignThis research shall assess the impact of foreign ownership to stock return volatility as a result of market liberalization. Moreover, the research shall cover a time span of five years. As this is a quantitative study, the hypothesis about the impact of foreign ownership on volatility of stock return in the Financial, Industrial, Holding Firms, Property, Service, and Mining & Oil Industry will be either rejected or not through statistical results; specifically, it will be done through a panel regression analysis. 4.2 Data Description and Collection Method

The data for this study will be sourced from several reliable databases. Particularly, this includes Philippine Stock Exchange (PSE), Securities and Exchange Commission, Bloomberg, and Osiris. A summary of such method of collection can be seen in the table below. Moreover, some variables, such as the Stock Return Volatility, Market Capitalization (LnMKTCAP), Leverage (LEV, and Lag of Stock Volatility (srvlag), will be subsequently computed once the values needed are completed.

The sample will have to be on a quarterly basis for years 2008, 2009, 2010, 2011, and 2012.

VariablesData Source

Independent VariableForeign Ownership(FO)Bloomberg

Dummy Variables (Sector)Financial Sector(FIN)Philippine Stock Exchange (PSE)

Industrial Sector(IND)

Holding Firms Sector(HOLD)

Service Sector(SER)

Mining and Oil Sector(MIN)

Property Sector(PRO)

Control VariablesDomestic financial institution ownership(DOMFIN)Bloomberg

Domestic non-financial institution ownership(DOMNONFIN)

Natural logarithm of market capitalization(LnMKTCAP)Osiris (natural logarithm will be generated through Stata)

Leverage(LEV)Bloomberg (subsequently calculated by authors)

Lag of volatility(srvlag)

4.3 Method of Data Analysis

4.3.1 RegressionAs previously stated, this study consists of both time-series (on monthly basis) and cross sectional data (different firms across all industries). Panel data, although seen to be an advantage, may show less significant and reliable estimates as the slopes and intercepts are held constant when the ordinary least square (OLS) estimation is used; thus, may lead to being a nave model. Moreover, it fails to account for heterogeneity among firms to be tested.

Fixed Effects Model (FEM) and Random Effects Model (REM) are two general regression techniques which can be used in order to avoid the preceding stated problems. In the results of the former model, it provides different intercepts but has a fixed slope entailing that the impact of one variable is the same for all. There are three least square dummy variable (LSDV) models under FEM: (1) LSDV1 capturing the unobserved heterogeneity in cross-sectional units as it presents the effects of time invariant variables, (2) LSDV2 capturing the unobserved heterogeneity in time periods as it presents the effects that are the same for all cross-sectional unit but different through time, and (3) LSDV3 which is a combination of LSDV1 and LSDV2 capturing the unobserved heterogeneity in both time and space. This information implies that LSDV1 and LSDV2 is a one-way fixed effects model, while LSDV3 is a two-way fixed effect model.

Conversely, REM accounts for unobserved heterogeneity using the error terms in both the cross-sectional units and time-periods. As an advantage, it allows for more degrees of freedom since it does not demean the data. Moreover, it is fit to be used for a data with a large sample ratio to its population. Hausman test will be used to assess which between FEM and REM is the best model for this study. It tests for the relationship of the regressors to the error terms; its null hypothesis states that REM is better, FEM otherwise.

4.3.2.1 Test for Stock Return Volatility

The relationship between foreign ownership and stock return volatility in the six major industries are examined through a regression framework. The dependent variable, in this case the stock return volatility for years 2008 to 2012, is computed by taking the standard deviation of the quarterly stock returns for each year.

The main variable FO is valued as a percentage calculated as the number of foreign owned shares divided by the total issued shares.

Depending on the previous test between FEM and REM, a regression will be run to test the relationship between the stock return volatility and Foreign Ownership (FO) while controlling variables which include domestic financial institution ownership (DOMFIN), domestic non-financial institution ownership (DOMNONFIN), natural logarithm of market capitalization (LnMKTCAP), leverage (LEV), lag of volatility (LagVOL), and trading turnover (TURNOVER). Dummy variables of each industry will also be included in the model.

The model will be utilized in a set of firms with foreign ownership and firms with no foreign ownership at all. Results from both will be compared to further emphasize the impact of foreign shareholding on firms. The research will make use of the data analysis and statistical software Stata to test the volatility of stock returns.

4.3.3 Post Tests

Since the data of this research paper is pooled, it implies that it consists of time-series data. In relation to this, it is essential to test for the stationarity of each variable (excluding dummy variables) due to a potential random walk characteristic often found in the said type of data. There are several types of panel unit root test, and in this paper, Fisher-type will be used. Its null hypothesis states that the tested variable is non-stationary and stationary otherwise.

Non-stationarity, on the other hand means that there are periods where the data is interrupted by a single event. The common non-stationary stochastic process in finance is the random walk model. It has a feature of a random walk wherein it incorporates all past shocks and has infinite memory. It tends to be unpredictable because the mean and variance are not constant; thus, it is needed to be corrected or adjusted.In the testing process, there are a few violations that should be noted so that the data set may be corrected. The violations are the following: heteroscedasticity, autocorrelation and multicollinearity of data.

Often found in cross-sectional unites, heteroscedasticity happens when the variances of the error terms are not constant and are unequal because of the different characteristics of the units/sample and in data collection. A data can be tested for heteroscedasticity using the Brusch-Pagan test wherein the null hypothesis states that it is homoscedastic; otherwise, it is heteroscedastic.

Autocorrelation is endemic in time series data wherein there is an existing relationship among the residuals or error terms. Any of the following may be done to test if such violation exists: find whether error terms are related over time using the Breusch-Godfrey test. In order to correct, you may find the missing variables such as lags or control variable or use Pearsons correlation coefficient.

In multicollinearity, violates the assumption that regressors are not related with each other. This tends to have two or more regressors which are linearly dependent. There are 4 types of MC; namely, complete absence (regressors are not linearly related at all), tolerable (a very small proportion of the regressand is jointly explained by both/all of the regressors), dangerous (a large proportion of the regressand is jointly explained by both/all regressors), and perfect multicollinearity (the regressors cannot explain the regressand individually).It can be detected using the Variance Inflation Factor (VIF) through Auxiliary regression which is a regression among the regressors. To correct this, data may be changed using the instrumental variable (estimated the average of the regressor using inputs of the average of instruments which are highly correlated with the regressor) or transformed or the sample size be increased.

For all regression models, Stata will be used in choosing which between FEM and REM will be fit, testing and correcting for violations, and evaluating the relationship among the variables.

4.4 Methodological Limitations

Although previous studies have estimated their model using monthly data, the researchers will incorporate data on a quarterly basis due to its unavailability. Additionally, instead of using two separate years and comparing them, in this study, we will be using 5 continuous years from 2008 to 2012 to increase the number of observations.

Even though the hausman test will be done which can be a ground for selecting between FEM or REM, the researchers may opt to choose latter over former because of the dummy variables (industries) which may be dropped as the latter demeans the data; thus removing such variables.

In cases where there may be an existence of omitted variable bias (OVB), the researchers will not include or add more variables which are originally not in the model since it can be argued that there are many other factors affecting the stock market and they cannot be all captured.

CHAPTER 5Results and Discussion5.1 Profile DescriptionINDUSTRYDESCRIPTION

FinancialIncludes firms engaged in banking, investments, and finance. More specifically, these firms generate profit through investing, lending, insurance, securities trading, and securities issuance activities.

IndustrialIncludes firms involved in manufacturing of products from raw materials, and is treated as the goods producing sector of the economy; more specifically, these firms generate profit through electricity, energy, power, water, food, beverage, tobacco, construction, infrastructure, allied services, chemicals, and diversified industrials.

HoldingsIncludes firms that control or manager partial or complete interest in another firm or firms. Usually Holding Firms do not produce the goods or service itself; rather. Its purpose is to own shares of other companies. These firms have great influence and control on the other firms decision-making team due to the voting stock they hold.

PropertyIncludes firms involved in land and property development. More specifically, these firms generate profit through selling or leasing real estate, which includes the land and anything permanently fixed to it such as houses, condominiums, townhouses, and retail store buildings.

Mining & OilIncludes companies engaged in mineral extraction, oil exploration, extraction and production. More specifically, these firms generate profit through, extraction and production of gold, silver, copper, lead, crude oil, natural gas, coal, other precious metals and stones, interests in petroleum contracts.

ServiceIncludes firms engaged in providing intangible products or services such as retail, transport, distribution, and food services, and is treated as the tertiary sector of the economy. More specifically, these firms generate profit through media, telecommunications, information technology, transportation services, hotel and leisure, education, and diversified services.

Source: Philippine Stock ExchangeSeveral models (Nave, LSDV1, LSDV2, LSDV3, and REM) can be applied in a pooled data. However, statistical tests must be done in order to identify which among them fits the specific model of the study. Although using OLS may present unreliable results as it reject unobserved heterogeneity, it must still be tested whether we should use the nave model. This has been compared with both the fixed effects model (FEM) and random effects model (REM). TABLE 2: NAVE, LSDV1, LSDV2, LSDV3, REM

P-VALUESUMMARY

Nave VS LSDV10.000LSDV1

Nave VS LSDV20.050Nave

Nave VS LSDV30.000LSDV3

LSDV1 VS LSDV3F = .100594591 < 1.56827614LSDV1

Nave VS REM0.000REM

FEM (LSDV3) VS REM0.000FEM

For actual statistical results, see appendices.Based on the results, it is better to use the LSDV1 and LSDV3 model rather than the nave model. On the other hand, as an OLS regression is compared to LSDV2, it prefers the former. In order to clarify which between LSDV1 and LSDV3 must be applied, a Walds test has been done where it shows that the latter is more appropriate for the model of the study. This implies that the unobserved heterogeneity for both time and space must be accounted. Between nave model and REM, the Breusch-Pagan test result shows that REM must be used. Finally, under the Hausman test where the least square dummy variable and random effects model are compared, LSDV3 (FEM) is preferred. However, as previously stated in the methodological limitation, the researchers opt to use the REM. Such choice is due to the fact that FEM demeans the data. This entails that the model will drop this studys dummy variables (six industries under the PSE) which are important to be estimated in answering the studys objectives. See appendices.Including time-invariant variables, or variables which does not change over time, allows us to identify and confirm that the differences among the entities has an influence on the dependent variable. In addition, REM allows for the inferences in the model to be generalized. The researchers believe that this is beneficial to the model given that our sample of 87 firms out of the firms listed in the Philippines Stock Exchange is large enough. Moreover, with an unbalanced panel where N (i.e. firms) is large and t (i.e. quarterly period) is small, REM is a more efficient estimator given the present data. TABLE 3: INITIAL PANEL REGRESSION

VARIABLECOEFFICIENTP-VALUE

fo2.5980910.025

dom-.44136750.408

hold-2.0172360.074

ind-0.93994060.364

min-1.3468060.305

prop-2.0803750.077

ser0.18799040.858

lnmktcap0.13289180.143

lev0.31864190.373

to-0.0018750.906

srvlag0.67814210.000

cons (fin)-1.254370.594

R-squared = 0.5164

For actual statistical results, see appendices.The result in above shows the coefficients and significance of each variable using the random effects model. As it can be inferred from Table 3, foreign ownership (fo) is significant with respect to stock return volatility (srv). However, it is against our a-priori expectation that there is a negative relationship between this particular independent variable and dependent variable. The possible reason behind such result will be discussed in the succeeding pages. Although domestic foreign ownership (dom), based on its p-value, is insignificant, its coefficient is in line with our a-priori expectation that as it increases (decreases), stock return volatility decreases (increases). In order to avoid the dummy variable trap, we had to omit one of the dummy variables. In this caase, we have omitted financial (fin) industry. Consequently, it now represents the constant (cons) which allows us to be able to compare the other industries. In this initial panel regression, we find that the financial (fin), holdings (hold), industrial (ind), mining & oil (min), and property (prop) industry are negatively insignificant as seen in its coefficients and p-values. Only the service industry showed a positive relationship with stock return volatility although it is insignificant as well.With respect to the models control variables, all are insignificant except the lag of stock return volatility (srvlag) which showed a positive relationship with the dependent variable. Moreover, the coefficients natural logarithm of market capitalization (lnmktcap) and turnover (to) were both against our a-priori expectation. On the other hand, leverages (lev) coefficient affirmed our expectation that the volatility of stock returns increases as the leverage ratio increases; thus, entailing their direct relationship.R-squared, which explains the goodness of fit, shows that 51.64% of the stock return volatility in this data (srv) is explained by the independent variables included in the model. The latter half which could explain the changes in stock return volatility could be a varying set of variables since this study touches the stock market wherein changes in this environment are affected by several factors.Given that this study has a panel data (total of 87 firms on a quarterly period) which typically includes the characteristics of a time-series data, a test for stationarity for each variable (excluding dummy variables) must be done in order to assure reliability of results from the final panel regression. Using the Fisher-type unit root tests, results for the stationarity of variables can be seen below.TABLE 1: TEST FOR STATIONARITY

VARIABLEP-VALUESUMMARY

srv0.000Stationary

fo0.000Stationary

dom0.000Stationary

lnmktcap0.3361Non-stationary

lev0.000Stationary

to0.000Stationary

srvlag0.000Stationary

For actual statistical results, see appendices.As shown in Table 1, the dependent variable, stock return volatility (srv), and independent variables, foreign ownership (fo), domestic ownership (dom), leverage (lev), turnover (to), and lag of stock return volatility (srvlag) are stationary except for the natural logarithm of market capitalization (lnmktcap). In order to correct this and to ascertain that the regression is not spurious, its first difference has been taken which has undergone the Fisher-type unit root test as well. Its results show that lnmktcap first difference is stationary with a p-value of 0.000 (see appendices). Similar to other studies, our data may violate certain assumptions. This implies that it is essential to test whether this studys variables are multicollinear, heteroscedastic, and autocorrelated. These may help to clarify as to why the previous initial panel regression presented such results.TABLE 4: Test for Violations

VIOLATIONRESULTS

MulticollinearityVIF Mean = 1.49Not multicollinear

HeteroscedasticityProb>F = 0.0000Heteroscedastic

AutocorrelationProb>F = 0.0000Autocorrelated

For actual statistical results, see appendices.As seen in Table 4, there exists tolerable multicollinearity in our model. This implies that the explanatory variables remain exogenous; thus, they are not severely related to each other. Given this, we may be able to interpret that each regressors independently explains the dependent variable. As it is inherent in a data containing several cross-sectional entities, the Breusch-Pagan test shows that the data is heteroscedastic. This means that its variances are not constant. This simply states that the firms in the sample, aside from being under different industries, have different characteristics. Lastly, the model is said to be autocorrelated according to the Woolridges Test implying that the errors are related with each other. Since error terms account for variables which are not in the model, this may subsequently mean that that there is an omitted variable bias (OVB). TABLE 5: FINAL PANEL REGRESSION (corrected)

VARIABLECOEFFICIENTP-VALUE

fo2.7340310.006

dom-0.40939370.085

hold-2.1464530.007

ind-1.0762240.217

min-1.4949030.026

prop-2.4538760.004

ser-0.02910870.965

dlnmktcap2.266010.300

lev0.32135570.016

to-0.00387410.090

srvlag0.68198020.000

cons (fin)1.6998440.017

R-squared = 0.5186

For actual statistical results, see appendices.In order to have a more robust analysis, we corrected the violations which existed in the model, namely, heteroscedasticity and autocorrelation. Moreover, we incorporated the first-differences natural logarithm of market capitalization (lnmktcap) as the Fisher-type test concludes that the actual lnmktcap is non-stationary. It can be observed from this corrected panel regression that certain variables which have been insignificant initially are now significant. As it can be seen in Table 5, the relationship of foreign ownership (fo) to stock return volatility (srv) remained significant with a positive coefficient of 2.734031. This implies that a percentage increase in foreign ownership may lead to a 2.734031 increase in stock return volatility. It means that the direct relationship between these two variables states foreign ownership tend to intensify the volatility of stock return of domestic firms. Although significant, this result is against our a-priori expectation that financial liberalization, which allows foreign investors to enter the markets, has a decreasing impact on aggregated total volatility (Aimpichaimongkol & Padungsaksawasdi, 2013). As previous studies have confirmed, these foreign investors becomes a benefit to domestic firms due to their demand of transparencies leading to less information asymmetry; thus, taking less risk (Wang, 2007 and Li et. al, 2010). Moreover, there is less reliance on debt financing as there is risk sharing with greater investor base. Lastly, they provide not only monetary capital but also technology and training of human capital which improves operational efficiency and performance of firms (Stilz, 2005, Mitton 2006, Lee and Huang, 2013, and Li et. al, 2010). These explanations imply that the impact of foreign investors on stock return and its volatility come from their intentions of getting returns from their investments by making changes internally. Consequently, based on the results, these cannot be applied in the case of the firms listed under the Philippine Stock Exchange. According to Bae and Chan (2001), when domestic stocks of emerging markets become available and accessible to the ownership of foreign investors, the return volatility of these investible stock become more volatile. As other studies have concluded, foreign investors may potentially speculate in the domestic market (Bailey et. al, 2008). Instead of long-term investments, foreign shareholders may only want to earn and gain by immediately buying and selling stocks once they view them to be at their lowest and highest price or when decreasing and increasing, respectively. It was defined by Kim and Wei (1999) as positive feedback trading. This may imply that foreign investors tend to acquire domestic stocks in order diversify their portfolio. This means that they are able to pool stocks from different countries where there is low correlation among the shares especially when it is put together in a portfolio with stocks from developed markets (Conover et. al, 2002 and Allen et. al, 2011). Such strategy may help them to have higher stock returns. However, as they immediately come and go from the market, it affects the value of companies shares since the aggregate stability of the market is shaken (Bekaert et. al, 2012). As foreign investors enter the domestic stock market, world market information are also absorbed and incorporated by the stock market (Ross, 1989) which affects its volatility; consequentially affecting the stock return volatility as well. These foreign investors who acquire or buy shareholdings from different firms increase the price of such stock as the demand drives up. Once information is completely reflected on the stock price, the shares held by these foreign investors may be sold by the same. This would lead to a drastic decrease on the stock price and the returns which may be gained from such share (Nyangoro, 2013). Since these are domestic firms, the aggregate domestic shareholders, may include controlling shareholders or those who may actually be the owners/directors/managers or simply those with high positions in the company. As it was done in the study of Li et. al (2010), they have concluded that these type of shareholders are long-term investors which may imply that they avoid excessive trading. Aside from this possible external role in the changes in stock return volatility, their influences in the management result to either high or low performance which may be reflected on the values of the shares. In a more positive note, Sun and Tong (2003) views those local controlling shareholders who have resources business knowledge lead them into making sound business decisions. With respect to public shareholders who do not have internal or management influence, theyre relationship with stock return volatility may be related to the interpretation of the other control variable, turnover. Despite these supporting statements to results of the regression and its affirmation on our a-priori expectation that domestic ownership is inversely related to stock return volatility with a coefficient of -0.4093937, it is seen to be insignificant with a p-value of 0.085. TABLE 6: SUMMARY STATISTICS

IndustrySRVFOMKTCAPLEVTO

FIN5.500.17105,024,759,314.930.760.0099

HOLD0.160.1461,133,362,567.630.790.0130

IND7.510.1751,548,315,509.970.450.0145

MIN0.930.1222,958,685,159.470.214.157106

PROP0.360.21121,887,343,515.480.560.0168

SER6.190.3335,661,542,188.290.440.0089

Table 5 shows that only the financial, holdings, mining & oil, and property industries which have foreign ownership are significantly related with stock return volatility. The firms which have foreign ownership under the financial industry, representing the constant or intercept variable, has a positive relationship with stock return volatility with a coefficient of 1.699844 and p-value of 0.017. Therefore, if there is an increase of firms with foreign ownership in this industry, the aggregate stock return volatility of this sector will increase as well. Although it can be seen that the mining & oil industrys coefficient is negative (-1.494903), using financial industry as a benchmark, the same with the latter, the former has a positive relationship with stock return volatility; thus, an increase of firms with foreign shareholders under the mining & oil industry leads to more volatility in their stock returns. These are the same with the industrial and service industry with coefficients of -1.076224 and -0.0291087, respectively (but insignificant). The holdings industry has a -2.146453 relationship with stock return volatility as compared to the financial industry (since it is set as a benchmark). Looking at the comparison of their coefficients, in this industry, as firms with foreign shareholders increase, their stock return volatility decreases; thus, there is a potential stabilization effect. This interpretation is similar with property industry given their coefficient of -2.453876 (but insignificant). Market capitalization (first differenced natural logarithm), which represents the size of firms, was seen to be playing a role in stock return volatility. Based on our results, although insignificant, this control variable is positively related to the dependent variable. It is against our a-priori expectation that firms which are relatively large tend to have less impact from volatility shocks (Cheung and Ng, 1992). The result implies that for every unit increase in market capitalization, stock return volatility may increase by 2.26601. This can be supported by the Nyangoro (2013) that when the domestic market is opened, foreign investors tend to have a higher proportion on the market capitalization. Another control variable, leverage, which is identified as one of the determinants of volatility, showed results where it confirmed this studys a-priori expectation. The significantly positive relationship implies that a percentage increase in leverage will lead to a 0.3213557 increase in stock return volatility. Highly leverage firm may entail that the firm is more inclined in debt financing (Zou and Adams, 2008); therefore, increasing equity risk. This is further clarified by Bhatti et. al (2010) wherein he finds that stock return volatility increases as systematic risk increases due to high leverage.As the nave view of the market (Brailsford, 1994), trading volume or turnover is seen to be positively related to stock return volatility as evidenced by Li et. al (2010). However, our results, though against our a-priori expectation, can be supported by Giot et.al (2010), Wang and Huang (2012), and Andersen et. als (2007) findings that there is higher return volatility but less turnover when investors view on a stock is the same given an information that sepreads throughout the market. Even when there might be a great number of shares bought or sold, given information, they may be in the same position; thus, stock prices and returns move in the same direction. Despite these evidences, turnover, in this data, is insignificant at the 95% confidence level in which Bailey et. al (2004) have tested that stock return volatility is not necessarily and completely affected by trading turnover. Finally, the lag of stock return volatility is positively significant with a coefficient of 0.681902. As Li et. al (2010) have stated, the lag of this studys dependent variable must be controlled as it is well known to be autocorrelated. This means that observations are likely to be correlated with its past observations.By correcting fore heteroscedasticity and autocorrelation, there was a slight increase of R-squared with a value of 0.5168. Similar to the preceding explanation, this panel regression has a satisfactory goodness of fit as it explains 51.86% of stock return volatility.

CHAPTER 6Conclusion and Recommendation6.1 ConclusionAs an emerging market, it is a concern on whether the Philippines must maximize potential benefits by completely opening its financial market to the world market or to put more restrictions with respect to financial liberalization. Due to mixed conclusions on the issues concerning the impact of foreign investors on stock return volatility, the paper mainly aims to identify the formers destabilizing or stabilizing relationship with latter using the listed firms in the Financial, Industrial, Holding Firms, Property, Service, and lastly the Mining & Oil Industry under the PSE from year 2008 until 2012. Out of the 296 firms listed under PSE, only 87 domestic listed firms have foreign shareholders (with complete and available data) and are therefore included in the study. Taking out the firms without foreign ownership enabled the researchers to assess the effect of foreign shareholders to the volatility of stock returns. As discussed in the preceding chapter, after certain variables have been controlled (i.e. domestic ownership, natural logarithm of market capitalization, leverage, turnover, and lag of stock return volatility), a percentage increase in foreign ownership may lead to an increase in stock return volatility, holding all other variables constant; thus, a positive relationship. Although contrary to the a-priori expectation that foreign shareholders stabilizes the volatility of stock returns, these type of investors do affect the volatility of stock returns but in a positive effect implying that it escalates and intensifies the volatility of domestic firms stock return. Rather than lessening information asymmetry, risk, and heightening efficiency and performance of the domestic firms through a monitoring role, foreign investors may only be investing in Philippine firms for speculation and in order for them to diversify their portfolio. These foreign shareholders may not be long-term investors and are only taking advantage of the rises and dips of the market to gain profit. Portfolio diversification may also be their goal as investing in different stock markets (i.e. developed markets and developing markets) can both lessen the risk and intensify the reward, depending on the economy and on the speculative strategies. 6.2 RecommendationThe researchers recommend that further studies concerning an in depth analysis of the investing behavior of foreign shareholders in the Philippine setting be done. By being able to assess whether these shareholders do fail to play a monitoring role in the firms that they invest in and instead merely play a speculators role, such a research can further prove the effect of foreign shareholders in the volatility of stock returns. However, it should be noted that the improvements in investment grades have only been recently received by the country; thus, further research is recommended using a different time period (i.e. future). Others may opt to choose a particular industry rather than all of the six in order for them to further scrutinize what foreign investors do in domestic firms. It is also recommended that the results of the effect of foreign shareholders in the Philippine stock market be compared with a country that has already been proved to receive a stabilizing effect from foreign shareholders. This would aim to answer and contrast the differences between the two countries to receive an opposite effect on the volatility of stock returns. Currently, given these results, it may be recommended that the entrance of foreign equity investors be monitored.

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APPENDICES:Test for Stationarity1) Stock return volatility. xtfisher srv

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 1048.8696 Prob > chi2 = 0.0000

2) Foreign ownership. xtfisher fo

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 437.0433 Prob > chi2 = 0.0000

3) Domestic ownership. xtfisher dom

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 316.7924 Prob > chi2 = 0.0000

4) Natural logarithm of market capitalization. xtfisher lnmktcap

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 181.3301 Prob > chi2 = 0.3361

. gen dlnmktcap = d.lnmktcap(388 missing values generated)

. xtfisher dlnmktcap (corrected)

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 1629.2059 Prob > chi2 = 0.0000

5) Leverage. xtfisher lev

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 395.1150 Prob > chi2 = 0.0000

6) Turnover. xtfisher to

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 987.5710 Prob > chi2 = 0.0000

7) Lag of stock return volatility. xtfisher srvlag

Fisher Test for panel unit root using an augmented Dickey-Fuller test (0 lags)

Ho: unit root

chi2(174) = 987.5064