Implications of insider trading rules on stock market efficiency : evidence on ASEAN-4

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Implications of Insider Trading Rules on Stock

Market Efficiency: Evidence on ASEAN-4

Department of Economics

Faculty of Economics and Business

Bachelor Thesis in Economics and Finance 2013

Author: Bagus Adi Yoga Prawira

Student Number: 10257551

Supervisor: Diana Hidalgo

Date of Submission: July 9, 2013

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I dedicated this thesis to my parents, Made Sudarta and I Gusti Agung Ayu Putri,

to my brother I Gde Bagus Arya Sumarapati and to my beloved Puspita Tarawati. I

am really grateful for their love being cherished throughout the writing process of

this thesis that has made me to put my effort at its best.

I also want to thank first my supervisor Diana Hidalgo for the helpful feedback

and supervision on the thesis writing process. Second, I would like to thank Andika

Perwira Mulya for the support on the statistical software used in the work of this

thesis. Their contributions have encouraged me in finding the interesting results.

I hope this work will be of much help for other colleagues interested in this area

and future researches…

Bagus Adi Yoga Prawira

Amsterdam, July 9, 2013

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Abstract

This paper examines the implications of insider trading rules on stock market efficiency in ASEAN-4 using a sample of 200 companies during 1988-2006. On average, it is found that a stricter insider trading rules is significantly associated with a more efficient stock market. This is also confirmed with the event study approach used in this paper showing that, in overall, the efficiency also increases in the firm-level stock prices after the initial enforcement. The results are robust after using alternatives measurement of stock market efficiency and numbers of regression specification. I also find that, the existence of creditor rights could deter the interests of minority investor that could lead to a less liquid market. I argue that, if the investor protection standard is increased controlling for this effect, it will only transfer more rights to the largest shareholders. This could make the manipulation of financial statement even worse and threatens the firms’ stock prices worthiness.

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1. Introduction

There has been a long debate between academics and policy makers for how the insider trading should be governed regarding its influences entailed on the financial market and economic performance of a nation, especially for ASEAN-4 as one of the emerging markets (Abumustafa and Nusair, 2010; Johnson et al., 2000). Manne (1966) and Carlton and Fischel (1983) argue about benefits that might be achieved by allowing the insider trading due to a more efficient stock market. That is by permitting it, stock price is expected to reflect more information and be higher on average and expected real investment will rise (Leland, 1992). However, since the insiders gain profits at these outside investor’s1 expense, it also might be true that the outside Investor will leave the market should there are more loss for them. These outside investors face asymmetric information since they are unfairly treated with regards to the signals of the prospective performance of the firms. This problem could be enough to drive the outside investors out from trading the securities in question, which will make the stocks being traded by insiders less liquid (Fishman and Hagerty, 1992; Fishman et al., 1998). The liquidity problem then may imply an inefficient stock market as it is derived from the sentiment of the investors regardless of the true value of the firm it self. At this stage, the proper way to rules the insider trading is needed to facilitate a more informative (efficient) stock market. This paper encounters these issues by trying to answer the following question. That is, how does the strictness of the insider trading rules could significantly affect the stock

market efficiency? It is expected by answering this question will give suggestions to the policy makers in

ASEAN-4 countries in authorizing the rules and institutional legal framework to ensure the participation of investor in the stock market.

As most of the insider trading opponents is the policy maker that argues for its negative effect on society welfare, all developed countries and most of developing countries having stock market have included this law into their enactment (Bhattacharya and Daouk, 2002). However, in ASEAN-4 countries, the effectiveness of having the insider trading rules is questionable. Even after the establishment and the enforcement of insider trading rules in these countries, there has not been any significant change in “price informativeness”2 in the stock market (Fernandes and Ferreira, 2008). While, the cost of equity seemed to be decreasing substantially only after the first enforcement (Bhattacharya and Daouk, 2002). The cost of equity it self could be the indirect measure for stock market efficiency that the lower it is, the more efficient the market is. In addition, Beny (2006) found a significant change on “price informativeness’ after the enforcement of the insider trading rules when using stock price synchronicity as the proxy.

1

The outside investor here is defined as any types of investor that do not own and trade the Inside information in the stock market.

2_{The “price informativeness” in Fernandes and Ferreira (2008) is defined as firm-specific return variation. This could be seen as one of the}

measurements of stock market efficiency, because it measures how much part of the firm-specific return explained by the stock prices. That is, how informative the stock price is.

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In the other side, the presence of strict insider trading rules in this market, in fact, generates a higher number of insider trading incidences when there is no sufficient regulations that ensure the fairness of investor rights (Durnev and Nain, 2005). They argue that, when there is a weak legal institution that favors the largest shareholder in the companies on top of the insider trading rules existence, the profits from insiders are simply being transferred to the ‘outside informed investors’3. This implies that to ensure the effectiveness of insider trading rules, one should consider the corporate governance environment that also protects the minority investor (Durnev and Nain, 2007; Beny, 2006). Nevertheless, its contribution to a more efficient stock market is still questionable since different measurement of it leads to substantial differences in conclusion.

To answer the previous question laid in the first paragraph, the multivariate regression analysis in country level is used as the first alternative and event study approach in firm level is used as the second. The purpose of the country-level study is to see whether the insider trading rules has significant effect on stock market efficiency in the macro field. While the firm-level study is used to check whether the similar implications derived for the efficiency in individual stocks. This is also to disentangle the endogeneity problem that may arise when only relying on country-level study. For the country-level study, the pooled OLS estimator is used after testing the Breusch-Pagan (1980) test (since this paper is dealing with longitudinal data). In the event study approach, the Difference-in-Difference estimate is used as suggested by many studies in looking on implications of policy changes (Card and Krueger, 1994; Abadie, 2005). Here, the average value of stock market efficiency variables will be compared between “before” and “after” the enforcement date (as a cutoff year or period) while controlling for other factors. To this respect, I want to look for the differences in stock market efficiency variables between the companies in the countries that have the enforcement policy (called the treatment group) and companies in the countries that do not have this policy (called the control group). This existence of enforcement policy signals a stricter insider trading rules regime.

In this paper, to represent the stock market efficiency variables, the theoretical model of stock’s expected abnormal return (measured by alpha-jensen measures) is used as the direct approach and Tobin’s Q and market liquidity as the indirect approach (see Gilchrist et al., 2005; Chordia et al., 2005, Fama, 1970). Alpha and market liquidity are only used in the firm-level and country-level study respectively due to data constraints. In computing the alpha, the Fama-French three-factor model is used instead of the CAPM as a benchmark. This is due to the additional risk factors included that can overcome the ‘anomalies’ occurred when using the CAPM (Fama and French 1996). The strictness of insider trading rules in this case is defined by some measurements that represent how strict it is (Bhattacharya and Daouk, 2002; Beny, 2005). In addition, to avoid the omitted variable bias, I also control for the corporate

3_{The outside informed investor here is defined as the outside Investor that owns and trade the Inside information on the Insider’s behalf.}

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governance’s environment and stock market and economic development in country level affecting the stock market efficiency (Beny, 2006; La Porta et al., 2006, 1998a; Levine and Zervos, 1996).

In the country-level study, I find that a stricter insider trading rules is associated with significant increase in stock market efficiency as shown by higher liquidity and less deviation of Q ratio to the parity in the stock market. This is also as predicted by Bhattacharya and Daouk (2002). The results are robust to alternatives regression specification, heteroskedastic-standard error, and different measurements of dependent variable. The possible endogeneity problem is encountered by using event study approach that also confirms the results in country-level study as shown by a lower absolute alpha values and deviation of Q ratio to the parity of individual firms in the countries that have been enforced. The results from firm-level study are also robust to the clustered-standard errors estimates and different group regression specification. I also find that a higher creditor rights could deter the interest of minority investor in the companies leading to a less liquid stock market. Whereas, the existence of higher creditor rights seems to be associated with a more efficient stock market. This effect, however, could results to the agency problem that corroborates the effectiveness of higher investor protection standard in avoiding the manipulation of financial statements done by the largest shareholders in the company. This, in turn, will pose a threat to the efficiency of the individual stock prices.

The data type adopted in this paper is a panel data across ASEAN-4 countries (Indonesia, Malaysia, Thailand, and Philippines) from 1988-2006. Most of the strictness of insider trading rules variables’ data are resurrected from Bhattacharya and Daouk (2002) and Beny (2005, 2007), and the rest (Stock market efficiency and control variables) will be collected on the basis of Individual Country Legislation, ASEAN stock exchange, IMF International Financial Statistics, Datastream and World Bank. ASEAN-4 countries are chosen instead of the ten countries after considering the economic importance and characteristics as emerging market4.

This paper then will be structured as follows. Section 2 will review the implications and theoretical framework used by the previous literatures including the gap between them, contributions that could be made and the hypothesis. Section 3 will explain about the sample data construction, variables and research methodology used in this paper with expected results shown from descriptive statistics. Section 4 is the main section, as it shows how the regression models are tested and infer the results. Section 5 will conclude the findings and discuss the limitations of the models employed and possibilities of future research.

4_{The ten members of ASEAN are Indonesia, Malaysia, Thailand, Philippines, Singapore, Myanmar, Cambodia, Brunei, Vietnam, and Laos. For}

more information see: http://en.wikipedia.org/wiki/Association_of_Southeast_Asian_Nations and

http://www.imf.org/external/pubs/ft/fandd/2006/06/country.htm

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2. Insider trading: The Presences and Hypothesis

How does the insider trading affect the stock market and economic performance of a nation? And more importantly perhaps, is the effect good or bad? In attempting to find the answers of these genuine questions, many empirical models have been uncovered and some contradicted to each other, leading to different positions with regards to the authorization of insider trading (Manne, 1966; Leland 1992; Fishman and Hagerty, 1992; Johnson et al., 2000). If the effect is bad (good), there will be more (less) opponents of Insider trading and the effective elements of insider trading laws would be imposed severely. Nevertheless, this bad and good outcome will be judged based on some “benchmarks”. If the stock market efficiency is the indicator here, the execution of the insider trading rules it self could probably give detrimental effect to the outcome. If some degrees of insider trading rules could significantly increase (decrease) the stock market efficiency, then we could say that perhaps the insider trading leads to a bad (good) outcome. However, this is without mentioning the limitations of assumptions made for measuring the stock market efficiency. Additionally, assessing the true impact of insider trading is a rigorous task. If the establishment of insider trading rules was in purpose to attract investors to participate in the more efficient stock market so that companies will be easier to get the capital, any activities that hinder it should be not miss-specified. Hence, by looking to the implications of insider trading it self on stock market efficiency and economic performance in theory and evidence based, we probably then could expect what to see when against it.

2.1. Insider Trading On Efficient Market Hypothesis

When speaking about insider trading, one does not simply ignore the benefits achieved (as individual investors) from it. Because, this benefit is the one that mainly motivates investors to participate in this activity (Keown and Pinkerton, 1981). The insider traders will buy (sell) the securities in question if they know that, based on the inside information, the firms will produce positive (negative) present value of investment in the future. This buy and sell will give return to the insider traders as they buy when the price is too low and sell otherwise. Since they can do it based on the inside information that is uninformed to the outside investor, it can generate abnormal return relatively to the average return in the market (Fama, 1970). In other words, the so-called arbitrage opportunity5 arises in the name of asymmetric information problems in the stock market and it favors whoever holds the inside information.

In the other hand, the Efficient Market Hypothesis proposes that all available information is reflected in the stock prices (Fama, 1970). This implies that the information regarding the past and

5_{Arbitrage opportunity exists when Investor can earn riskless return without making a net investment. Often referred as free lunch. See Body. Z,}

Kane, A. and Marcus, Alan J. Investment9h _{Ed. (New York: McGraw Hill-Irwin, 2011): 324.}

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expected future performance of the firms are already incorporated into the stock prices and represent its true value (Grossman and Stiglitz, 1980). This is related to a random-walk theory stating that because the stock prices has fully incorporated all information, its movement will be unpredictable and only can be affected by newly updated news regarding the securities in question (Kendall and Bradford, 1953; Malkiel 2003).

The Efficient Market Hypothesis itself is divided into three forms according to some extent that the stock prices include the information (see Fama, 1970). The weak form states that only publicly past historical data are reflected in the prices6. The semi-strong form assumes all publicly information is reflected7. While in the strong form, assumes that all information including the inside information regarding the future prospects of the firms is incorporated into the stock prices8. This suggests that to test whether the market is strong form efficient, we should assess whether by trading based on the private information (called as insider trading) could generate abnormal return (Fama, 1991).

In a simplified world, should the insiders who trade on this information could gain abnormal return, then it could be that the market is at least not strong form efficient (Grossman and Stiglitz, 1980). Nevertheless, it is adjustable if not theoretically proven to take the transaction cost into account for a more sensible picture in which more complication arises (Jensen, 1978). Moreover, when one to test the efficiency forms of the market to some extent by whether the insiders can generate abnormal return based on some particular information, the results could be biased with relation to the skills possessed by the investor it self. If there is no or less abnormal return gained by these traders, it could be also that they fail to include the information properly into their investment strategies and yet the market could be not strong form efficient. In the other side, even if the stock price is not efficient and arbitrage opportunity actually exists, there are limitations to exploit it (De long et al., 1990). These limitations are related to some risks that prevent the arbitrageurs9 to exploit the mispricing. These risks are fundamental risk, risk in cost when implementing the strategy, and risk contained in the model used when building the strategy (see Schleifer and Vishny, 1997). Hence, in this paper measures the stock market efficiency not by looking on the investors abnormal return that pursue the actively-managed portfolio strategies10, but by directly looking into the implications of the market value or stock prices of individual firms in micro and macro level.11

6_{Ibid., at 347.} 7_{Ibid., at 347.}

8_{Ibid., at 348.}

9_{There is a slight difference in defining the arbitrageurs between academics and practitioners. Academics assume a strict sense of pure}

arbitrageurs who are the investors that try to find a risk-less profit from mispricing, while practitioners commonly refer it as risk arbitrage where the investors actually pursue a risky strategy. In here, I refer it as both terms. See supra note 5 at 323-324.

10_{Actively managed portfolio is the strategy implemented by investors in chasing the possible mispricing among securities prices. The}

participants of this strategy sometimes called as arbitrageurs. This comprises any type of investors including the insiders. See supra note 5 at 350-351.

11_{The term ‘micro’ and ‘macro’ here are referred to as efficiency in individual level stock prices and broad market level stock price respectively.}

Although the two terms are commonly used in one meaning to imply the stock market efficiency, in practical concern, each term could give different implications. It could be that the market as a whole is efficient but not in the firm level. This could be caused by the aggregated efficiencies in the market level, leaving to the possibilities of having many less influential stock that are not efficient.

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2.2. Insider Trading on Stock Market and Economic Evidence

The presence of insider trading in the concept of Finance’s microstructure seems to be intriguing the fact of its realization in economic statistically means. In fact, its implications on abnormal return possibilities were found to be more than theoretically speaking (Meulbroek, 1992). As some of the evidence suggest, these returns were observed across major stock market in the world and especially during the significant economic phenomena (see Abumustafa and Nusair, 2011; Johnson et al., 2000). For example when crash and booms, the movements in expected future performance of the firm would be more sensitive than what the current stock price ‘says’. In this state, inside information will have more value, since there will be a larger jumps or drops of stock prices than is expected by the ‘uninformed’ average investor in the market. The arbitrage opportunity profit is expected to be high even after the trading cost is included and survived as long as the up-to-date stock prices has not fully reflected the true value of the firm (see Durnev and Nain, 2005).

As highlighted by Meulbroek (1992), the insider trading was found to be preceding the largest stock movements. However, the interesting part is that, the insider’s ‘sells’12 strategies had much more appearances several months before the large drops in the stock prices in individual stock level (Marin and Olivier, 2008). It seems that insider’s “sells” pattern could lead to a crash in the economy (Marin and Olivier, 2008). Despite the difference in the samples used, these findings were undoubtedly related to the “contribution” of insider trading during the 2008 Financial Crisis in NYSE and KSE. The abnormal return gained by insiders was observed in NYSE and KSE from the start of the crisis in 2007 until the mid of 2008 (just before the peak of the crisis) with an average of 4.5% above S&P 500, and 1.4% above KSE index respectively (Abumustafa and Nusair 2011). Nevertheless, at the end of 2007, the situation was reversed and the insider’s portfolio underperformed the market index on average by 2.54% in NYSE and 3.36% in KSE. This is actually as expected by Marin and Olivier (2008) that the insider trading activity preceded the largest stock market movement and market participants were not that rational in assessing the pattern of insider trading. The insider’s ‘sells’ and ‘purchase’ have made the impression of the ‘not so bad’ firms were looked to be really bad, and when the market realized it, it was already too late. As a result, by the end of 2008, it has indirectly contributed to the 50% decline of Dow Jones Industrial Average in United States and in some emerging stock markets (like Saudi Arabia and UAE by losses of 70% and 80% respectively) through its affection on market sentiment (Abumustafa and Nusair, 2011).

The similar conclusion was derived for ASEAN-4 countries (Indonesia, Malaysia, Thailand and Philippines) in which there seems to be a negative relation between corporate governance and the economic performance during the 1998 East Asian Financial Crisis (Johnson et al., 2000). These

12_{Insider sells is the Insider’s portfolio consisting of strategies selling the securities that are expected to be decreasing in price in the following}

months based on Inside information (see Marin and Olivier, 2008).

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countries were found to be having poor corporate governance prior to the crisis that could be seen from a less financial transparency, minimum legal protection to minority investors and large cash flow rights from largest shareholders (La Porta et al., 1999b). In fact, given the political environment in these countries, the attributions of poor corporate governance could lead to a mass insider trading activity. The largest shareholders that have more rights to manipulate the financial statements could create the ‘imaginative’ future’s firm values without significant supervision. The effect was not that soundly in normal times, but when the crisis hit the economy, the expropriation and manipulation of financial statements became much more feasible (Johnson et al., 2000). As a result, there was a shock on outside investor confidence leading to a huge capital outflow from the market (Jonshon et al., 2000). Unfortunately, it also sent negative signals for domestic and foreign investors in the real sectors that loosing their confidence on published financial statements of the firms they invest and pulling their money out of it. In turn, it yielded a depreciation of exchange rates on most of these countries from 50% to 500% and a lowest IFC investable index by the end of 1998 (Johnson et al., 2000). In this case, the insider trading activity was truly deepening and folding the impact of the crisis on these countries as a follow-up of poor corporate governance effect.

However, regardless of its significance in empirical models, some suggest the benefits of insider trading that might be achieved by allowing it (Glosten, 1989). Some researches argued that the permission of insider trading would lead to ambiguous welfare effect that depends on the economic environment. When insider trading is allowed, stock prices tend to reflect more information in the short-run and be higher on average, more profits for Insiders (more positive welfare effect if the majority of participants in the stock market is the insiders or their associates), and easiness for firms in looking for capital (Leland, 1992). Nevertheless, this is not enough to ensure the positive welfare effect as in the medium-run, market become less liquid, expected real investment moves in ambiguity and outside investors is hurt more since their expected return is being cut by the asymmetric information problems (Fishman and Hagerty, 1992, 1998).

In overall, the single answer seems to be unsettled that whether insider trading leads to majority good or bad outcome. However, if the more outside investor in the market could not get the pattern from insider trading rationally and the information being “traded” on insider trading is not really a correct future’s value of the firm, the market could be much less efficient since prices will be more volatile and could deter the efficiency of capital allocation in which one majority welfare effect could be sided (see Dow and Gorton, 1997). Hence in this paper, it will be searching for answers of how the insider trading should be governed in order to enhance the market efficiency. Of course some legal attributions surrounding the scope of insider trading should be considered to make sure things established properly.

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This is because the authorization of insider trading it self was found to be not satisfactory in ASEAN-4 countries as will be covered in the next sub-section.

2.3. Insider Trading Rules in ASEAN-4

The implications of insider trading on evidence based have surely attracted the needs of its governance. In fact, from 22 developed countries and 81 emerging markets that were found to be having stock market by the end of 1998, 100% and 80% of it have had the insider trading laws on their enactment respectively (Bhattacharya and Daouk, 2002). In ASEAN-4, Malaysia was found to be the first that had the insider trading law and Indonesia was the last (1973 and 1991 respectively). As Bhattacharya and Daouk (2002) suggests that the mere existence of insider trading rules could not deter the incidence of insider trading, we will be focusing on whether there is a prosecution with regards to insider trading rules violation in legal court. In that shed of light, Bhattacharya and Douk (2002) found that 82% of the developed countries and 23% of emerging markets have had the prosecution policy until today. Based on their research, in ASEAN-4, only three out of them that have been enforced (Only Philippines that was found to have no prosecution within the sample period). The enforcement of this rule in all over the world including ASEAN-4 in beginning of 90’s was seen to be the phenomena (Bhattacharya and Daouk, 2002). This trend in ASEAN-4 could be caused by the premature anticipation with regards to poor legal institution in siding the huge capital inflow by that time. Since the poor corporate governance’s environment is positively linked with underdeveloped stock market, these countries tried to make sure that investor could participate fairly in their developing stock market (La Porta et al, 1997). However, these actions might have been too late as the deepening crisis relieved the truth of immature financial system in these countries (Johnson et al., 2000). It is also apparent that the authorization of insider trading rules in this market leaves an ambiguous answer among many literatures.

Fernandes and Ferreira (2008), by using panel regression and event study approach, attempted to look for changes of “price informativeness” and cost of equity after the enforcement of insider trading rules. This “price informativeness” could be seen as measurement for market efficiency, since it measures the firm-specific return that is not explained by the market. They found that, in ASEAN-4, the enforcement policy of insider trading rules has only significantly reduced the cost of equity. However, they used the CAPM as the benchmark when calculating the “price informativeness” in which was severely criticized due to its unsolved ‘anomalies’ that the results could be tentative and less reliable (Fama and French, 1996). Whereas, the similar conclusion expressed by Bhattacharya and Daouk (2002) that after using the same event study approach in four different measurements, the enforcement of insider trading rules has significantly reduced the cost of equity. The decrease in cost of equity gives some importance into this paper, since it signifies the required return (after risk premium included) perceived

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by the market. If the cost of equity is lower, it means the risk involved regarding the asymmetric information in the stock market could also be lower that indicates a more efficient stock market.

However, when the stock market efficiency is measured differently, the insider trading rules is found to be associated with a more efficient stock market (Beny, 2006). She used stock price synchronicity as a proxy for “price informativeness” that was found to be evitable in measuring the firm-specific return variation (Morck et al., 2000). A lower firm-firm-specific return variation implies that smaller proportion of individual stock return’s variation explained by the market than the firm-specific part. It suggests that individual stock prices contain more information about firm’s strength and weaknesses (Beny, 2007). Nevertheless, this firm-specific return variation could also be affected by other additional risk factors such as liquidity, value and size premium (Fama and French, 1996). By only taking measurement based on the total firm-specific return, we still cannot separate its true abnormal return with return that is caused by additional premium required in accordance to the nature of the firms it self. Despite of the models used as a measurement for market efficiency, it is also interesting to find the specific environment needed to facilitate the conduction of insider trading rules it self. It is because that different legal framework could lead to different implications of insider trading rules indirectly.

In this manner, Durnev and Nain (2005) tried to find the effect of stringent insider trading rules on insider trading incidences. They found that a stricter insider trading law, in fact, induces more private information traded when the country is having a high ownership wedge13 and weak investor protection. At this stage, in the presence of insider trading laws, the largest shareholders that have more rights could expropriate and hide more the information from minority investors and transfer it to their associates that are not tied to the rules. This will allow them to trade in huge amount and generate a higher return for private information trading (La porta et al., 1999b). While, Beny (2007) found that the equity ownership outside the firms is positively linked with the strictness of insider trading rules that generates a more transparent disclosure and lessens insider’s incentives to trade. However, Beny (2007) did not test for the causality linkage that might be involved reversely in which less outside equity ownership could cause the needs for stricter insider trading rules. In either way, it is probably true that the authorization of insider trading in ASEAN-4 countries has been disappointing and deviating from its desired outcome in terms of private information traded incidences.

More interestingly, the insiders seem to trade with less reluctance when the penalty imposed is damaging only for a large movement in ex-post stock prices (Fishman and Hagerty, 1998). In this case, the insiders would trade more actively based on news that generate moderate impact to stock prices movement only. Thereafter, the conformation of significant sanction and criminal justification toward any

13_{Ownership wedge here is defined as the difference between control rights and the cash flow rights held by largest shareholders. Higher control}

rights of largest shareholders could increase the expropriation and manipulation of financial statements for their benefits that make the disclosure of published financial statements of the firms less transparent and trustable. See Durnev and Nain (2004, 2005).

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kind of insider trading should, probably, be more regulated if we want the authorization of insider trading rules does not flaw. However, the same justification toward different magnitude of impact from insider trading could lead to protests from its proponents (that is, the largest shareholders in big firms), in which in ASEAN-4 countries, the less government’s respect to private property rights make this regulation less binding (Fernandes and Ferreira, 2008). If the government values less on private rights (in this case, the uninformed investor14 rights), the establishment of the insider trading rule itself will be one-sided that quietly favors the bigger party that has more rights. However, the important implication is that if insider trading rules were made in purpose to attract investors to participate in the market by ensuring less asymmetric information trading-based, that is to reduce the cost of asymmetric information, one should mitigate the protection of minority investor in addition to a better corporate governance to make sure that the uninformed investors are fairly treated and interested to invest in the stock market (see La Porta et al., 1997, 1998, 1999b).

2.4. The Hypothesis

So far we have been faced by two major problems in the stock market related to insider trading and its prohibition. First, the asymmetric information problem was related to the loss of outside investor, profits of insiders, and ambiguous informational efficiency. While for the second, the agency cost only represents the loss that occurs when the corporate governance in question is inadequate in facilitating the insider trading rules that lead to more expropriation by insiders in a weak investor protection standard environment. Whereas, the insider trading could be the cheap way in transferring the information with respect to future prospect of the firm to the market without really disclosing it materially before its official time (Manne, 1966; Leland, 1992). Rather than prohibiting it to trade and delaying the ‘disclosure’ of the information to stock prices, insider trading would reveal it prematurely and cheaply (Carlton and Fischel 1983; Manne, 1966). In this case, asymmetric information could lead to majority benefits and outweigh the agency cost. However, this relies on big assumption that if the investors are rational, which will threaten the benefits achieved from asymmetric information.

Unfortunately, investors are not rational and some of them even trade based on their mood and preferences contributing to a less efficient market even before taking the insider trading effect into account (Chopra, Lakonishok and Ritter, 1992; Statman, 1997). If insider trading is allowed, the insiders will function as the ‘rational’ party that knows true information regarding the current stock prices and step in the market should there are inefficiencies in pricing. However, the overreaction and correction of investor’s irrationality with respect to insider trading pattern could make the market more volatile and vulnerable to any significant news (Bond and Thaler, 1987; Shefrin and Statman, 1985). This will make

14_{The term ‘Uninformed Investor’ here is used interchangeably with ‘outside investor’.}

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the stock market less attractive for the outside investor to participate leading to a less liquid market after the short-run (Fishman and Hagerty, 1998). This less liquid market will instead make it more difficult for arbitrageurs to exploit the mispricing occurrences, since trading the stocks in question is not possible given its availability in the market. If that is the case, the arbitrageurs behaving as rational party will fail to convert the individual stock prices to be efficient and the market as a whole will remain inefficient as long as the investors are not motivated to be rational.

Despite the profit possibilities generated for either the insiders or any other investors in the market that behave as arbitrageurs, there are apparent losses borne by other citizens, namely, lower returns for uninformed investors and inefficient capital allocation. If there is mispricing, the overpriced firms will get the capital relatively cheaper and the underpriced firm might forego some investment opportunities, since now they have to raise the capital more costly. In the capitalist economy, this will delay the generating process of real investment in the economy regardless the current stance of monetary and fiscal policy as the real resource allocation are mostly affected by equity market15. At this stage, the inefficient stock market could deter the economic efficiency and even more the long-run economic growth (Levin and Zervos, 1996; Caporale et al., 2004). Therefore, ensuring stock market efficiency is one of the big interests here. To achieve that, the insider trading rules could be one of the tools. However, we know that the existence and the prosecution of the insider trading rules it self were not sufficient to effectively reduce the private information traded, at least for ASEAN-4 countries (see Durnev and Nain, 2005, 2007; Fernandes and Ferreira, 2008). Nevertheless, the main concern here is to look on insider trading rules implications on stock market efficiency and not on whether it does effectively reduce the incidence of private information traded.

If the private information traded could not be deterred, the efficiency in individual stock level (micro field) would probably be difficult to pursue. However, the existence of insider trading rules and its enforcement could show a good impression on outside investor to participate in the market that will make it more liquid. This more liquid market will make it easier for the arbitrageurs and induce them to step in the market should there are some mispricing in individual stock prices. In other cases, there will be more investors that will rationally perceive this as a signal in pursuing a more efficient stock market and adjust their expectation accordingly. Then, there will be less time for the whole market to be inefficient as long as there are enough rational investors that would wash out the irrational ones (Fama, 1991). Hence, I

hypothesize that a stricter insider trading rules is associated with an increase in the stock market efficiency both in the market and firm level. Before testing it with regression analysis, these measurements

of stock market efficiency and insider trading rules will be described first below.

15_{See supra note 5 at 352.}

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3. Description of the Data and Methodology

This section will describe how the sample variable constructed, which empirical models used and expected results shown by descriptive statistics. The sample consists of 200 companies from four countries (Indonesia, Malaysia, Thailand, and Philippines considered as ASEAN-4) that were chosen after considering the economic importance implied in ASEAN economy within period of 1988-2006. However, I drop the ones that have randomly missing values and inactive period within 1988-2006. In Figure 1, it shows the overall trend of stock market development across the four countries. Notice that it excludes Singapore since its value is extremely high compared to these four countries and including it in the same figure will be incomparable16. In Figure 2, it shows the overall trend of economic size of ASEAN countries measured by GDP. Notice that it excludes Myanmar due to the data unavailability. As we can see that based on economic importance (GDP), the four countries (Indonesia, Malaysia, Thailand, and Philippines) are in the top 5 (including Singapore). However, when comparing the stock market development among these five countries, Singapore has a much more developed stock market. Hence, in this paper, ASEAN-4 is chosen as I want to focus more on countries as emerging market that have similar economic and stock market characteristics and trends. The other interest of choosing countries within ASEAN is based on the personal preference that my home country is Indonesia.

Figure 1. Stock Market Development

This figure shows the overall trend of stock market development for the four countries from 1991-2006 as measured by Stock Market Capitalization of listed companies over GDP. As we can see that in overall, despite for Malaysia in 1991-1996, the four countries are in the same level and moving in the same direction. Data source:

http://databank.worldbank.org/data/views/reports/tableview.aspx#

16_{The ratio of stock market capitalization over GDP for Singapore lies between 100-200, which is incomparable to the four countries. The data}

are available from: http://www.worldbank.org/

M ar ke t C ap ital iz at io n/ GD P Year Indonesia Malaysia Thailand Philippines

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Figure 2. Economic Size (GDP)

This figure shows the overall trends of the size of economy among ASEAN countries from 1991-2006 excluding Myanmar due the data availability. The economic size of the top 5 countries (Indonesia, Malaysia, Thailand, Philippines and Singapore) are at

least twice bigger than the other 4 countries leaving Lao PDR to be almost touching the zero level. Data source:

http://databank.worldbank.org/data/views/reports/tableview.aspx#

3.1. The Stock Market Efficiency Variables

Because there is no direct data that can quantify the stock market efficiency directly, it will be measured by using three proxies. The first one, the stock market efficiency is measured using alpha-jensen measure17 as the direct proxy. The alpha measures the abnormal return of the securities when comparing its actual return to a benchmark computed based on asset-pricing model18. If the market is efficient, assuming that the asset-pricing model used is valid, then the actual return of the securities should be matched with what is predicted by the model (alpha is zero). This is because that the model used is expected to contain all information regarding risk factors that signifies the true value of the securities (Sharpe, 1964). If, however, the alpha is non-zero values, it implies that the stock prices moves differently in actuality compared to what should be predicted by the benchmark (Jensen, 1968). This means that there are some information that are not reflected yet in the stock prices which make the investor to either bid the securities too high or too low leading to an existence of abnormal return for a

17_{Alpha-jensen measure is mostly used to evaluate the performance of risky portfolio of investment funds instead of only single securities. The}

use of alpha in evaluating the performance of the investment funds is to measure whether the risky portfolio under- or over-performs the market. However, in this paper, the use of alpha is referred to as measurement for deviations of individual actual stock prices to its true values. Both will give implications for whether the stock prices follows a random-walk model and unpredictability of return (the market is efficient). If the alpha implies that the risky portfolio of investment funds can generate abnormal return (hence, outperforms the market), then there is predictability of stock return since there are some trends or patterns that are not fully reflected in the prices (the market is not efficient). See Jensen (1968); Malkiel (1973, 2003).

18_{See supra note 7 at 353.}

G DP ( in c ur re nt U S$ ) Year Singapore Brunei Darussalam Cambodia Lao PDR Malaysia Indonesia Philippines Thailand Vietnam

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given securities19. This abnormal return could measure the market efficiency, that is, the higher abnormal return in absolute value means the larger deviation of the stock prices from its true values and the market is less efficient. Because this alpha directly measures the deviation of the stock prices to its true value, it is considered as one of commonly accepted as direct measure of stock market efficiency.

In this paper, the Fama-French Three-Factor model from Fama and French (1993,1996) is used as a benchmark in computing the alpha values of each company. This is chosen instead of CAPM (that was commonly used) because it can overcome the ‘anomalies’ occurred related to the value-growth stocks premium and size effect20 when using CAPM as the benchmark (see Fama and French, 1996). The Fama-French Three-Factor model includes two risk factors, which are SMB and HML (excess return of the portfolio consisting small size firm to portfolio consisting big size firm and excess return of portfolio consisting High Book-to-Market value firms to portfolio consisting low Book-to-Market value firms respectively) as addition to RM (excess return of the market portfolio to risk-free rate) used in CAPM. These two additional risk factors were found to be more capable in explaining the average return on stocks (Fama and French, 1993). The specification of the Fama-French Three-Factor model and alpha formula regarding the expected return and abnormal return of individual stocks are specified below:

(1) E(Ri,t) – rfs,t = Bmi,t (Rms,t – rfs,t) + Bsi,t (SMBs,t) + Bvi,t (HMLs,t)

(2) E(Ri,t) = rfs,t + Bmi,t (Rms,t – rfs,t) + Bsi,t (SMBs,t) + Bvi,t (HMLs,t) (Rearranged from eq.1) (3) Alpha = Ri,t – (E(Ri,t))

Where i is individual stocks, s is stock market of the country, t is period, ER is expected return, R is actual return, Alpha is abnormal return, rf is risk-free rate, and Rm is market portfolio return. While Bm, Bs, and

Bv are the beta of the individual stocks that measures its return sensitivity to return of the market, size and

book-to-market value (or often called as value stocks) portfolio respectively. Because there are no data regarding investment companies that invest with portfolio style of size and value stocks until before 2005, the portfolio for each style is formed using the data of the companies in each country from the sample. To calculate the SMB, first the portfolio consisting firms based on its size siding with its actual return are arranged and the return differences of small and big size firms are calculated. For HML, the same procedure is done as in calculating the SMB. In this case the portfolio is formed based on book-to-market value from high to low and the return differences are calculated. For RM, it is just simply the return differences between the market index portfolio (JSX, Bursa Malaysia Index, SET, and PSEi) and the

risk-19_{One should not confuse about this relationship. It is not that the existences of non-zero alpha values lead to the mispricing of the securities by}

the investor, but the other way around. See Hummers (1986).

20

“Value” stock is stock with low P/E ratio and High Book-to-Market Value. This stock tends to have higher return than “growth” stocks that have the reverse characteristics. “Size” effect implies that smaller size firms measured by its market capitalization tend to have higher return than bigger firms. Whereas, this is due to the premium required to compensate the investor to hold the small firm that has less information. The anomalies occurred when controlling for these two factors, the beta of the market seemed to have less significant explanatory power to the stock return. See more of this relationship and other anomalies in Fama and French (1992, 1993).

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free rate in each country. From there, the computation is made for the beta (with slope function), expected return (with FF-Three Factor model), and the alpha for each company.

The data regarding the companies’ stock prices, number of shares traded, market value, book value, stock market indices, and risk-free rate in the country are annualized from 1988-200621. The data are collected from Datastream, Worldscope, and IMF International Financial Statistics22. However, as I am interested to use the alpha as a measurement of deviation of stock prices to its true value, the alpha is converted into absolute terms (since the alpha could be negative). This form of alpha will be the one that is used in this paper and defined as EFF. In this case the lower of this value will indicate a lower deviation of stock prices to its true value and hence the market is more efficient. In the regression, however, the logarithm of alpha is used instead and defined as LOGEFF to ease the interpretation of the results. This is because that the absolute alpha values imply a direct proxy for market efficiency that is really difficult be quantified in which the measurement in fixed value can give a less reliable meaning.

For the second proxy, the Tobin’s Q is used as a base model. This ratio reflects the deviation of the price in which the asset is traded in the market with its carrying value or replacement cost of capital (Tobin, 1969). The use of Tobin’s Q was mostly done in real investment determination. However, it could give additional implications related to the stock market efficiency. The Q ratio is not only determined by computation made by accountants and statisticians regarding the book value of an asset but also by the investor sentiment about the future’s prospect of the firm that is implied in the nominator of the ratio (market value) (Tobin, 1969). If the Q ratio is more (less) than parity (Q>1 and (Q<1) respectively), the price of an asset traded is higher (lower) in the market than what should have been to acquire (the replacement cost of capital). In this case, the investor will try to sell (buy) the asset and drives down (up) the prices until the Q ratio returns to the parity (Q is approaching to 1). The most determinant that generates Q ratio to be less or more than parity is the fluctuation in the market value that is affected by market expectation and rationalities towards the securities in question. Whereas the replacement cost of capital will represent the fundamental values of the firm (Tobin, 1969; Summers, 1986)). Hence, the more deviation from parity will imply a less efficient market. However, because the replacement cost of capital or the book value computed in the Tobin’s Q model is the fundamental value that comes from published financial statements, its deviation from parity will only represent how semi-strong form efficient the market is23. Therefore, this measurement is considered as indirect, since it does not include the specification of inside information. As I am interested in looking into the deviation of what the market

21_{There are some companies that only have either annually or quarterly data in the beginning of the sample period, and the risk-free rate is only}

available in annual term. Hence, I choose to make all data to be annualized to ease the operation of the data. The data that covers from 1988-2006 in companies and stock market level is only for Thailand since its first enforcement date is in 1993 and I want to start at least 5 years before that year to allow a longer time window in estimating the relationship between market efficiency and Insider trading rules.

22_{The data are available on:}_{http://www.econstats.com/ifs/NorGSc_Ind2_Y.htm} 23_{See again Fama (1970).}

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perceives to the fundamental value of an asset, the difference between Q ratio observed for each company with the parity is computed in absolute term and defined here as DEV. In this case, the lower it is, the lower the deviation of the market value24 of an asset to its fundamental values and the more efficient the market is. However, with the same reasoning in the use of absolute alpha value, the form logarithm form is used and defined here as LOGDEV. This is because that it shows how efficient the stock prices with relation to the semi-strong form efficient in which is difficult to be quantified in fixed value.

The third proxy for the stock market efficiency will be the market liquidity. This is the alternative of indirect measure of stock market efficiency, as the more liquid stock market could imply a more efficient stock market indirectly (Chordia et al., 2005). If the market is liquid enough, it will facilitate the arbitrageurs in exploiting the arbitrage opportunity that will bid the price up or down until emerging to its true value25 (the market becomes efficient) (see Chordia et al., 2008; Schleifer and Vishny, 1997). However, Chordia et al. (2005, 2008) use the bid-ask spread as a measurement for market liquidity in which these data are not available for my sample countries. Hence, the stock market value traded GDP ratio is used for a proxy of market liquidity as suggested by Caporale et al. (2004) and Levine and Zervos (1996). This measure will be defined as LIQ and represented in terms of ratio where the higher it is the more liquid the market is. The data are in annual terms collected from World Bank26 for sample period of 1991-2006 for each country. In the regression, the logarithm form is used since I want to estimate its change in percentage term to ease the interpretation.

Figure 3 shows the trends between average value of DEV and LIQ across all country. As expected, despite the possible weak correlation observed, the two lines seem to move in different direction synchronically. That is, when the market becomes more liquid (AVG LIQ goes up), the deviation of stock prices to its fundamental values is decreasing (AVG DEV goes down) and hence is more efficient toward the semi-strong form. Of course, without testing its significance, we cannot really emphasize for which one that trigger the other one. However, this is not relevant to my concern, since looking on market liquidity can give sufficient implications for whether the market is already efficient or will be efficient. In overall trend, the movements of the two lines indicate a more efficient market through times.

3.2. The Insider Trading Rules And Control Variables

Since all of the four countries have had the insider trading rules on their enactment, I do not include the variable indicating the availability of the rules into the empirical models used here. Whereas,

24_{In this case the term “market value” can loosely be used interchangeably with stock prices, as both give information on how much an asset}

being traded in the market.

25

One should be careful with this relationship that it is not necessarily true for a more efficient market to be caused by a more liquid market. Since the more efficient market could also lead to a more liquid market. The market liquidity here should not be seen as the primary cause of efficient market, but only as one of the attributes or characteristics of the efficient market. See more about this relationship on Fama (1970); Bhattacharya and Daouk (2002); Chordia et al. (2008).

26_{The data are resurrected from:}_{http://databank.worldbank.org/data/home.aspx}

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the insider trading rules is based on an index implying how strict it is in each country. I use the combined index that is aggregated by Beny (2005, 2007), Durnev and Nain (2005), and Bhattacharya and Daouk (2002). The index is formed by adding one from each of the following conditions if: (1) tippees (corporate insiders) are prohibited from trading on price-sensitive private information; (2) insiders are prohibited to give price-sensitive private information to the outsiders (called tippee); (3) the insider trading is a criminal offense in the country; (4) the potential monetary penalties to the violation of insider trading laws are higher than the insider trading profit; (5) Investors have a private right of action; (6) There has been an enforcement or prosecution towards the insider trading rules violation that is justified in the legal court. From condition (1) to (5) is defined as ITREG and for condition (6) is defined as ENFORCE. The sum of these two will be defined as INS and used in the empirical model here that has a scale from 0 to 6. The higher it is, the stricter the insider trading rule is.

Since the stock market efficiency, as documented by previous studies, could also be enhanced by proper corporate governance and other macro factors through its channel in propagating the financial development, I control for these variables in the regressions (see La Porta et al., 1997, 1998a; Fernandes and Ferreira, 2008; Levine and Zervos, 1996; Jin and Myers, 2006; Beny, 2006, and 2007; Durnev and Nain, 2005, 2007). For the corporate governance environment, first I control for the investor protection. This is the aggregated index of anti-director rights from La Porta et al. (1998a) based on what is listed on each countries enactment regarding the company’s code. This investor protection index is defined as

PROT here that has a scale from 0 to 6. A higher score means a more protection for the shareholders

(especially for the minority investor) and higher private property rights. Second, in corresponds to investor protection that represents the shareholder rights, I also control for the creditor rights to see the true effect of insider trading rules when these two rights collide that may relates to agency problem. As the common jargon in companies’ policies issues, favoring the rights between shareholders or creditors will be more likely to deter to each other’s rights (La Porta et al., 2006). This will be the aggregated index from La Porta et al. (1998a) with original data come from Bankruptcy and Reorganization Laws listed on the enactment of each country. It has the scale from 0 to 4 and defined here as CRED. A higher rights for creditors may give a good signal to the stock market participant in which the stock prices will be less volatile due to the a less risk-taking project pursued by the corporate managers (Acharya et al., 2011; Djankov et al., 2008). This will lessen the market expectations about the stock prices and hence its deviation to its true value is expected to be lower.

Finally, I control for other macro factors in country level that contribute to a greater financial development in association with a more efficient stock market. First, since the economic growth contributes to a more developed financial market and better institutional and law enforcement quality, I control for logarithm of GDP per capita (see La porta et al. (1981); Caporale et al. (2004); Beny (2007).

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This variable is defined here as LOGGROWTH. The data are collected from World Bank WDI database from 1988 to 2006 in annual term. Second, I control for the logarithm stock market capitalization of listed companies over GDP that represents the stock development of a country. This is because that a more developed stock market is associated with a more liquid and efficient stock market (Levine and Zervos, 1996)27. This variable is defined here as LOGSTOCK. The data are in annual term from 1988 to 2006 and the source of this data is World Bank WDI database.

The detail summary description of all variables explained above is presented in Illustration 1 (in the appendix).

Figure 3. This figure shows the trends between average market liquidity (measured by AVG LIQ) and average deviation of

firms’ market value to its fundamental value (measured by AVG DEV) of the four countries from 1991-2006.

3.3. The Empirical Setup

To test the hypothesis in this paper, the multivariate regression is used using first the dependent variable in country level. The purpose of using the dependent variable in country level here is to look whether the insider trading rules has significant effect on stock market efficiency in macro terms. This country-level study does not use the absolute alpha values (hence, only market liquidity and absolute deviation of Q ratio) due to the unavailability of the data required to compute the alpha in annual terms. While the computation of deviation Q ratio to the parity in country level is the averaged value of companies in the sample for each country. The main specification of the empirical model used is specified below:

(4) LOGDEVc or LOGLIQc = α + β1INSc + β2PROTc + β3CREDc + ΦkZkc + ε

27_{Notice that in Levine and Zervos (1996), market liquidity and market capitalization over GDP are two of the proxies for stock market}

development. However, market liquidity is the only stock market development characteristic that could represent the stock market efficiency more closely. Hence, in this case controlling for market capitalization over GDP will contribute more to overcome the omitted-variable bias arise when determining the relationship between stock market efficiency and Insider trading rules.

AVG D EV, A VG LI Q Year AVG LIQ AVQ DEV

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Where c is for country indexes, α is the constant term, ε is the error term and Z’s are other country-level control variables. It is expected that the coefficient of β1 will be negative and positive for when the dependent variable is LOGDEV and LOGLIQ respectively. β2 and β3 may have different implication on the dependent variables. A higher investor protection standard is desired when one want to avoid the expropriation done by corporate managers. However, the more rights that the creditor has could also make the other stakeholder’s rights to be jeopardized (in this case is the investor). In this case, the strength of the effect of insider trading rules on stock market efficiency is tested given these two detrimental factors on companies’ policies.

Considering the fact that this paper deals with longitudinal or panel data, a random-effect model was initially chosen as also suggested by some of the previous studies (Fernandes and Ferreira, 2008; Durnev and Nain, 2007). This is due to the preference in looking the effect from possible time-invariant variables within entity (Hausman, 1978). However after testing the Breusch-Pagan (1980) test, the null hypothesis is not rejected with 10% significance level implying that there is no significant differences across entities (or the variation of random effect is not significantly different from 0) and a pooled OLS estimator can be used. Hence, this paper uses the simple OLS regression to quantify the effect of insider trading rules on stock market efficiency for dependent variable in country level.

However, relying on this regression only, the endogeneity problem could arise in the name of possible reverse causality relationship between stock market efficiency and strictness of insider trading rules and other omitted factors that are unobserved. A less efficient stock market may mitigate the needs of stricter insider trading rules caused by the probable inefficient stock prices effect from insider trading activity. One way to disentangle this problem is to use the event study approach. In this case, the Difference-in-Difference estimates using OLS regression is used as suggested by some of the previous studies in looking on implications of policy changes (Card and Krueger, 1994; Abadie, 2005). The main concern here is that whether the first enforcement towards the insider trading rules violation could enhance a more efficient stock market. This enforcement gives indication of the seriousness of the government in authorizing the insider trading rules. Here, the firm-level dependent variable is used in purpose to isolate the significant change that occurs within each country that is probably unobserved when estimating the effect across countries. In this shed of light, the average stock market efficiency variables in firm level are compared for “before” and “after” the cutoff period (the enforcement date of each country). For Thailand, as the first enforcement occurred in 1993, this will be the cutoff year. While for Indonesia and Malaysia that have enforcement year of 1996, after considering also the exogenous effect from 1998 East Asian Crisis, will have the cutoff period of 1996 to 1999. The main reason to focus on the first enforcement is that it will give implications of the first policy changes that this will allow to estimate the true effect while isolating the other unobserved effect. Of course, by using this method, one

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should make another assumption that ties to all entities. It requires that across entities should have the similar trends and characteristics in which it would stay the same as if there have been no enforcement in any of the four countries. Looking to the similar trends and characteristics in stock market development and economic size as shown in Figure 1, one could argue for this assumption to hold at least for a given sample period. In addition, the close distance between each country and similar cultural values and background as ASEAN countries would convince the assumptions made for the Difference-in-Difference estimates to be used.

Since in this case Philippines as the only country that will not have enforcement through the sample period, this will be the comparison for the other three countries. The treatment variable will be the one indicating whether the companies in the country that will have an enforcement or not (equal 1 if yes and 0 otherwise). Because in this case, the regression will only take two periods, the “before” and “after” enforcement date will be the period 1 and 2 respectively for each country. For each period will take the average value of 4 to 5 years window to allow a significant difference observed for each country. The firm-level dependent variables used here are logarithm of absolute alpha values and the logarithm absolute deviation in Q ratio to the parity (explained in the previous section) for each company in each country. The specification of this regression is elaborated below:

(5) LOGEFFi or LOGDEVi = α + β1TREATMENTi + β2ENFi + β3ENFxTREATMENTi + ΦkXk c _{+ ε}

Where i is for the individual companies, TREATMENT is for the dummy variable that has a value of 1 for the companies in the country that will have an enforcement and 0 otherwise, ENF is for the dummy variable that has a value of 1 for “after” period and 0 otherwise, and X is the control variables. Notice that, the interaction term of ENFxTREATMENT is included. The coefficient of this variable will be the one that is looked for, since it estimates the real effect on stock market efficiency variables for companies in the country that will have an enforcement in the “after” (or post-enforcement) period. For this regression, I test first by including Indonesia, Malaysia, and Thailand together in comparison to Philippines assuming that they have the same trends for the “before” and “after” period. Then I test Thailand separately in comparison to Philippines since Thailand has different enforcement date and hence different “before” and “after” period. This is done to ensure the assumptions regarding similar trends among entities being compared.

3.4. The Descriptive Statistics

Table 1 illustrates the summary statistics of the main variables for each country used in the country-level study. In overall, for the time periods of 1991 to 2006, Malaysia had the most liquid and efficient stock market and Philippines had the least one (as shown by LIQ and DEV). This is probably still

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with the conjunction that countries with stricter laws will have a more efficient stock market. In overall, Malaysia has the strictest insider trading laws and corporate governance with a score of 4 in INS, PROT, and CRED. While Philippines, despite the high investor protection standard, it scores low on insider trading rules (INS) and creditor rights (2 and 0 respectively). Indonesia, although it has a less strict insider trading rules and investor protection standard than Thailand, seemed to have a more efficient stock market as measured by DEV and LOGDEV. This could be due to a more significant effect from high creditor rights in this country signaling a good impression to the stock market for the validity of the firm’s information listed on the stock exchanges. However, a really high creditor rights could deter the effect from investor protection standard on market liquidity as this country still relies more on loans from banks in financing the projects. Additionally, Philippines, despite the fact that it has a higher investor protection standard than Indonesia, the non-existence of enforcement of insider trading laws might hinder the effectiveness of investor protection standard in protecting the minority investor from expropriation done by the insiders. So far, this is as expected by the hypothesis that a stricter insider trading rules and better corporate governance (measured by a higher score between the two rights) are aligned with more liquid and semi-strong form efficient stock market. However, this is still without testing its significance and taking the other macro factors into account that also contribute to stock market efficiency.

Table 2 presents the pair-wise correlation matrix among all variables that are in conjunction with the empirical model used in the country-level dependent variable regression. As expected by the hypothesis, the correlation between INS and LOGDEV is negative and significant at 10% level implying that countries with stricter insider trading rules have a more semi-strong form efficient stock market. Additionally, the correlation between INS and LOGLIQ is positive and significant at 10% level indicating that countries with stricter insider trading rules have more efficient stock market through liquidity. In the other side, the correlation coefficient of PROT and CRED to LOGDEV and LOGLIQ implies that indeed countries with better corporate governance have a more efficient stock market as measured by the deviation of Q ratio from the parity and market liquidity. However, the coefficient correlation of PROT to

LOGDEV is negative but not significant at 10% level implying that there might be other unobserved

institutional factors that might affect the behavior of this variable. One should also notice the interesting fact that countries with higher creditor rights have less investor protection standard and the other way around as shown by negative correlation between PROT and CRED. The agency problem seems to collide here. When the creditors have more rights in the companies, the protection of investors seems to be deterred. Moving to other macro factors (economic and stock market development), countries with a more developed economy tend to have a less liquid stock market that is shown from the negative correlation between LOGGROWTH and LOGLIQ that is significant at 10% level. This could be due to the fact that the GDP used in the measurement of economic development (GDP per capita) is the denominator in the

Implications of insider trading rules on stock market efficiency : evidence on ASEAN-4