Information Efficiency and Anomalies in Asian Equity Markets

Theories and evidence

Qaiser Munir, Sook Ching Kok, Qaiser Munir, Sook Ching Kok

• Publisher: Routledge
• Year: 2016
• Print ISBN: 9780367595920
• eBook ISBN: 9781317270294
• Edition: 1
• Topic: Economics
• Subtopic: Economic Theory
• Index: Economics

The efficient market hypothesis (EMH) maintains that all relevant information is fully and immediately reflected in stock prices and that investors will obtain an equilibrium rate of return. The EMH has far reaching implications for capital allocation, stock price prediction, and the effectiveness of specific trading strategies. Equity market anomalies reflect that the market is inefficient and hence, contradicts the EMH.

This book gathers both theoretical and practical perspectives, by including research issues, methodological approaches, practical case studies, uses of new policy and other points of view related to equity market efficiency to help address the future challenges facing the global equity markets and economies. Information Efficiency and Anomalies in Asian Equity Markets: Theories and evidence is an insightful resource that will be useful for students, academics and professionals alike.

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Equity market informational efficiency

History and development

Qaiser Munir and Sook Ching Kok

1.0 Introduction

In economics and finance, the term ‘efficiency’ has several distinct connotations. This term can be used to refer to allocation efficiency, informational efficiency, operational efficiency or technical efficiency.¹ At the outset, it is necessary to clarify that in this chapter ‘efficiency’ only refers to informational efficiency, such that prices are based on the best available information (Howell and Bain, 2005: 540). According to Latham (1986), the most common implicit definition for informational efficiency is that prices will not change if all private information is publicized. Zou (2011) interprets this type of efficiency as the effectiveness of market information.

As such, an efficient market, as it is generally understood and practiced, is a market in which investors are unable to earn consistent excess profits from trading stocks. Fama (1970) precisely defines an efficient market as one in which security prices fully reflect available information. Earlier, Fama (1965) stated that an efficient market should contain a sufficiently large number of participants who are rational profit-maximizers and have almost free access to all relevant information. Their competition causes stock prices to incorporate information promptly. Beechey, Gruen and Vickery (2000) believe that efficient markets adjust instantaneously to new information. According to Malkiel (2003), efficient markets are devices that reflect new information quickly and for the most part accurately. In such markets, therefore, investors are not likely to anticipate the future direction of security prices. Even good analysts cannot outwit the market. Thus, it is possible for investors to obtain an above average return without taking an above average risk.

It is well acknowledged that the fundamental principle of all gambling is simply equal conditions. This idea was addressed by the Italian mathematician Girolamo Cardano in Liber Aleae, or The Book of Games of Chance, published in 1564. Another landmark event in the history of EMH was the discovery of Brownian motion in 1828 by the Scottish botanist Robert Brown. He noticed that grains of pollen suspended in water display quick oscillatory motion. As articulated in 1863 by the French stockbroker Jules Regnault, security price deviation is directly proportional to the square root of time. According to Regnault, as in a game of heads or tails, stock price movements are independent (Jovanovic and Gall, 2001). In 1888, the British logician and philosopher John Venn explained the concepts of random walk and Brownian motion. The term ‘efficient markets’ was probably first mentioned clearly in a book entitled The Stock Markets of London, Paris and New York, which was published in 1889 and written by George Gibson. A breakthrough in the history of EMH was made by Louis Bachelier, a French mathematician. In his PhD thesis published in 1900, he developed the mathematics and statistics of Brownian motion (Bachelier, 2006). At that time, his work did not gain much attention (Sewell, 2011). In 1905, the Einstein’s theory was introduced and provided a better understanding of the formulation of diffusion equation for Brownian particles and diffusion coefficient to measurable physical quantities (Berkyürek, 2012). In the same year, a professor and fellow of the Royal Society, Karl Pearson (1905), in Nature described a random walk as the drunkard’s walk. Samuelson (1965) explained the coherence of randomness in stock price movements and efficient markets under the martingale property. In 1965, the two landmark studies of Eugene Fama were published. Fama (1965b) explained how the theory of random walks could pose a great challenge to both technical, or chartist, analysis and fundamental analysis. Meanwhile, Fama (1965a) discussed random walk theory and empirically validated the random walk model. Following the definitive paper of Fama (1970) on the theory of efficient capital markets, the EMH raised a fast-growing interest among researchers, market practitioners, and analysts. In 1991, Fama acknowledged new dimensions of return predictability as part of the weak-form tests, in addition to the more established tests for the predictive power of historical stock prices. Timmermann and Granger (2004) discussed the EMH from the perspective of the modern forecast approach. He postulated the self-destruction of predictability; that is, stable predictable patterns will disappear when they are known to the public and have been extensively exploited.

On the other hand, the validity of market efficiency was criticized in a number of prominent studies. In their findings, Kemp and Reid (1971) showed that stock price movements were conspicuously nonrandom in short time horizons. Hence, it was argued that those findings of randomness in stock price movements could be changed by the method of analysis. Grossman and Stiglitz (1980) assert that perfect informational efficiency is unlikely to hold true, as information costs will limit arbitrage activities. Moreover, Andersen (1983–84) views equity markets as highly imperfect but liable to speculative manias. Furthermore, stock prices are perceived to be too volatile to accord with efficient markets (LeRoy and Porter, 1981; Shiller, 1981). Bondt and Thaler (1985, 1987) discovered market inefficiencies that correspond to the overreaction hypothesis. The finding suggests that overreaction to unexpected news or events is a key feature of equity markets. Jegadeesh and Titman (1993) demonstrated the profitability of momentum-based investing strategies. The finding is clearly different from the outcome of an efficient market, since the momentum effect is the idea that investors usually underreact to firms’ earnings information, causing price continuation (Barberis, Shleifer and Vishny, 1997). According to Wilson and Marashdeh (2007), the observed short-run arbitrage opportunities attributed to cointegrated stock prices are evidence against the EMH. However, it is clarified by Fama (1998) that anomalies are chance results that tend to disappear with changes in technique. In the opinion of Malkiel (2003), equity markets are actually more efficient and less predictable than they are thought to be in certain studies. More recently, the financial crisis of 2008–2009 seems to cast some doubt on the validity of market efficiency. In response to this particular issue, Ball (2009) stresses that it is important to understand the basic premise, applicability, and limitations of the EMH; he defends the hypothesis.²

Notwithstanding, the EMH is extensively applied in many current studies. This hypothesis has remained vital in dictating the behaviour of stock prices. Today, it is still intact and continues to attract much research interest. Against this background, we aim to give an overview of the underlying theories and core concepts in the field of equity market informational efficiency and to provide a broad picture of this research area. We focus on the intellectual history of EMH to trace the origins and development of theories and empirical works. The remainder of this chapter is organized as follows: Section 2.0 presents efficient market theories; Section 3.0 discusses the EMH and its implications; Section 4.0 explains technical analysis; Section 5.0 illuminates fundamental analysis; Section 6.0 reviews developing trends in the EMH literature. The last section presents our conclusions.

2.0 Efficient market theories

2.1 Theory of efficient capital markets

The underlying idea of equity market efficiency is based on the theory of efficient capital markets and the EMH defined in Fama (1970). The theory has three important assumptions: first, security trading has zero transaction cost; second, information is at no cost to all market participants; third, all participants agree on the implications of current information for current prices and the distributions of future prices for every security. Once the above conditions are fulfilled, it is impossible for the market to be efficient. In fact, this theory is built on the foundation of rational expectations. Muth (1961) describes rational expectations as the optimal forecast using all available information (Muth, 1961). The idea of this theory is expressed in three related models, including the fair game expected returns model, the sub-martingale model, and the random walk model. Equation 1 below shows the fair game model:

$$E\left({\tilde{P}}_{j,t+1}\mid {\Phi }_t\right)=\left[1+E\left({\tilde{r}}_{j,t+1}\mid {\Phi }_t\right)P_{jt}\right],$$

(1.1)

where E is the expected value operator, P_jt is the price of security j at time t, P_{j, t+1} is the price of security j at time t + 1, r_{j, t+1} is the one-period percentage return on security j, $\frac{p_{j,t+1}-p_{jt}}{p_{jt}}$, and Φ_t denotes any information set which is fully reflected in the price of security j at time t, P_jt. In this model, market equilibrium is expressed in terms of expected return as a function of risk conditioned on the relevant information set. In more detail, security price at time t + 1, P_{j, t+1}, and the one-period percentage return on security, r_j,t₊₁, are two random variables that are subject to being changed by the information reflected in security price at time t, P_jt. As such, the current price of security fully reflects all available information. This model implies that it is impossible to have any trading systems that relies only on the information set Ft to outperform the market.

An integral part of the efficient capital markets theory is expressed using the sub-martingale model. Equation 2, which follows, shows the model:

$$E\left({\tilde{P}}_{j,t+1}\mid {\Phi }_t\right)\ge P_{jt};+E\left({\tilde{r}}_{j,t+1}\mid {\Phi }_t\right)\ge 0.$$

(1.2)

This model indicates that the expected return of security conditioned on the information set Φ_t is nonnegative. If the expected price of security for the next period exceeds its current price, the price sequence P_jt is said to follow a sub-martingale, whereas if the expected price of security for the next period is equal to its current price, then the price sequence of security follows a martingale. As implied from this model, those trading systems that are based only on the information set Φ_t are unable to provide returns on security greater than the equilibrium return.

It is usual for the word ‘martingale’ to refer to the strap of...

Table of contents

• Cover
• Title
• Copyright
• Contents
• List of figures
• List of tables
• Notes on contributors
• Preface
• Acknowledgements
• 1 Equity market informational efficiency: history and development
• 2 Equity market anomalies: concepts, classifications, theories and evidence
• 3 The random walk hypothesis on the small and medium capitalized segment of the Indian stock market
• 4 Stock market index price prediction using predetermined variables: a case study of Malaysia
• 5 A re-examination of the calendar anomalies during the Asian financial crisis: some empirical evidence from the closure test principle and the EGARCH–mean model
• 6 The mean reversion effect and the contrarian strategy
• 7 The momentum effect: pricing paradox or new beta strategy
• 8 Momentum returns, market states and financial crises: evidence from China and Hong Kong
• 9 The profitability of technical trading rules: empirical application on Asian stock markets
• 10 Technical trading and market efficiency in Asian equity markets
• 11 Testing for semi-strong efficiency under stressed market conditions: a comparative focus on Asia, Europe and the United States
• 12 Technical efficiency and stock performance of listed commercial banks in ASEAN-5
• 13 Asymmetric effect of political elections on stock returns and volatility in Malaysia
• Index