An empirical analysis of the weak-form efficiency of stock markets
2017-01-13T00:46:04Z (GMT) by
The main objective of this thesis is to show that additional insights, beyond the verdict of market efficiency/inefficiency, can be obtained from those existing statistical tests of the weak-form efficient markets hypothesis (EMH). As an introduction, Chapter 1 provides the background and outline of this thesis. Chapter 2 then surveys the relevant literature and discusses the motivations behind the development of the three key research questions addressed in Chapter 3 through 5, respectively. Chapter 3 examines the association between trade liberalization and the weak-form efficiency of stock market, motivated by the production-based asset pricing model of Basu and Morey [Trade opening and the behavior of emerging stock market prices, Journal of Economic Integration 20(1), 2005, 68-92]. Using data from 23 developing countries over the sample period of 1992-2006, we find that a greater level of de facto trade openness is associated with a higher degree of informational efficiency in these emerging stock markets, even after controlling for trading volume and market return volatility. Further analyses find no significant association between the extent of financial openness and the degree of informational efficiency. While Chapter 3 provides novel evidence on the association between trade openness and stock market efficiency, our empirical work can also be viewed as addressing the issue of whether the existing theoretical determinants (i.e. trading volume, return volatility, trade liberalization and financial openness) are capable of explaining the variations of index return autocorrelations across countries and over time. Chapter 4 employs the rolling bicorrelation test to measure the degree of nonlinear departures from a random walk for aggregate stock price indices of 50 countries over the common sample period of 1995-2005. We find that stock markets in economies with low per capita GDP in general experience more frequent price deviations than those in the high income group. Our results consistently show that this clustering effect can largely be attributed to low income economies providing weak protection for private property rights. We conjecture that weak protection deters the participation of informed arbitrageurs, leaving those markets being dominated by sentiment-prone noise traders whose correlated trading cause stock prices in emerging markets to deviate from the random walk benchmarks for persistent periods of time. Chapter 5 proposes a novel framework to explore the direct relationship between stock return autocorrelations and news events. We first apply the wild bootstrapped automatic variance ratio test to detect significant serial correlations in the 1-minute transaction returns of the Kuala Lumpur Composite Index (KLCI) for each trading day. Our results show that only 141 out of the total 373 trading days during the Asian crisis exhibit significant return autocorrelations at the 1% level. A subsequent event matching procedure reveals that 29 trading days with significant return autocorrelations can be associated with major market-moving media events, which we hypothesize is due to a higher level of information uncertainty. Thirty seven percent of the trading days with significant return autocorrelations cannot be explained by any economic or political news, which we interpret as indicative of investors’ herding behavior not driven by information. Chapter 6 summarizes the key findings of this thesis along with some recommendations for future research. Finally, we conclude this thesis by offering some general guides which might be useful for future empirical research on stock market efficiency.