Kian-Ping Lim

THE EVOLUTION OF STOCK MARKET EFFICIENCY OVER TIME: A SURVEY OF THE EMPIRICAL LITERATURE

This paper provides a systematic review of the weak-form market efficiency literature that examines return predictability from past price changes, with an exclusive focus on the stock markets. Our survey shows that the bulk of the empirical studies examine whether the stock market under study is or is not weak-form efficient in the absolute sense, assuming that the level of market efficiency remains unchanged throughout the estimation period. However, the possibility of time-varying weak-form market efficiency has received increasing attention in recent years. We categorize these emerging studies based on the research framework adopted, namely non-overlapping sub-period analysis, time-varying parameter model and rolling estimation window. An encouraging development is that the documented empirical evidence of evolving stock return predictability can be rationalized within the framework of the adaptive markets hypothesis.

Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests

This article re-examines the evidence of return predictability for three major US stock indices using two recently developed data-driven tests, namely the automatic portmanteau Box–Pierce test and the wild bootstrapped automatic variance ratio test. In tracking the time variation of return predictability via rolling estimation window, we find that those periods with significant return autocorrelations can largely be associated with major exogenous events. Theoretically, the documented time varying nature of predictable patterns is consistent with the adaptive markets hypothesis.

The Weak-form Efficiency of Chinese Stock Markets Thin Trading, Nonlinearity and Episodic Serial Dependencies

Motivated by the shortcomings of earlier Chinese efficiency studies, the present paper re-examines the weak-form efficiency of Shanghai and Shenzhen Stock Exchanges. Specifically, our adopted methodologies mitigate the confounding effect of thin trading on return autocorrelation, detect both linear and nonlinear serial dependencies in the adjusted returns series, and capture the persistence of dependency structures over time. The result shows that the adjusted returns series from both markets follow a random walk for long periods of time, only to be interspersed with brief periods of strong linear and/or nonlinear dependency structures. This suggests that there are certain time periods when new information is not fully reflected into stock prices. Another interesting finding is that the existence of serial dependencies in both the Shanghai and Shenzhen Stock Exchanges follows one another closely after October 1997. It indicates that both markets respond in a similar way to influences from political, economic, social and institutional changes.

Are Chinese stock markets efficient? Further evidence from a battery of nonlinearity tests

Given that the efficiency of the Chinese stock markets was empirically examined in extant literature using statistical tests that are designed to uncover linear correlations of price changes, the obtained statistical inferences of efficiency/inefficiency are on very shaky grounds as highlighted in a recent article by Saadi et al. (2006). Motivated by this concern, the present article re-examines the efficiency of the A- and B-shares markets in Shanghai and Shenzhen Stock Exchanges (SHSE and SZSE) using a battery of nonlinearity tests. The empirical investigation reveals strong evidence of nonlinear serial dependence in the underlying returns generating processes for all indices even after removing linear serial correlations from the data, hence, contradicting the unpredictable criterion of weak-form efficient market hypothesis. Theoretically, these results are not surprising given the fact that investors in the Chinese stock markets trade like noise traders, who purely speculate and treat the market like a casino.

Statistical Inadequacy of GARCH Models for Asian Stock Markets Evidence and Implications

This study employs the Hinich portmanteau bicorrelation test (Hinich 1996; Hinich and Patterson 1995) as a diagnostic tool to determine the adequacy of Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models for eight Asian stock markets. The bicorrelation test results demonstrate that this type of model cannot provide an adequate characterisation for the underlying process of all the selected Asian stock markets. Further investigation using the windowed test procedure reveals that the violation of the covariance stationarity assumption as required by the GARCH process is due to the presence of transient epochs of dependencies in the data. The inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolios selection, development of optimal hedging techniques and risk management.

Foreign direct investment, financial development, and economic growth: the case of Malaysia

This paper presents, within an endogenous growth model, an analysis of the interaction between foreign direct investment (FDI) and financial development in promoting Malaysias economic growth. Using a co-integration framework, this study estimates a dynamic endogenous growth function that includes the impact of FDI and financial sector evolution as well as some locational determinants for the sample period spanning from 1970 to 2001. The empirical evidence suggests that foreign direct investment, labour, investment, and government expenditure play a pivotal role in local economic prosperity. More importantly, it is found that the interaction between FDI and financial development exerts a significant effect on the growth performance of Malaysia. Perhaps the strongest result to emerge from our study is the significant role played by FDI–finance interaction in the growth process.

Weak-form market efficiency and nonlinearity: evidence from Middle East and African stock indices

This study examines the existence of nonlinear serial dependence in five stock markets in the Middle East and Africa. The results from the application of a battery of nonlinearity tests reveal that after removing all short-term linear dependence, the stock returns still contain predictable nonlinearities that contradict the unpredictable criterion of weak-form efficient markets hypothesis.

Non-Linear Predictability In G7 Stock Index Returns

This paper re‐examines the persistence and source of non‐linear predictability in the stock markets of G7 countries. Applying the Brock–Dechert–Scheinkman (BDS) test on autoregression (AR)‐filtered returns in rolling estimation windows, we find evidence of local non‐linear predictability in all the sampled stock markets. To identify the source, we apply the BDS test on AR‐generalized autoregressive conditional heteroskedasticity (GARCH)‐filtered returns in rolling windows. After accounting for conditional heteroskedasticity, we still find brief time periods with non‐linear predictability in all markets, contradicting the weak‐form efficient markets hypothesis.

Nonlinear mean reversion in stock prices: evidence from Asian markets

Utilizing the standard linearity test of Luukkonen et al. (1988), the linear nature of all the Asian stock indices has been formally rejected. This finding warrants use of the nonlinear stationary test of Kapetanois et al . (2003), which is also constructed in the STAR framework, to investigate the mean reverting property of the stock prices series. As a whole, this study not only found convincing evidence of a nonlinear mean reverting pattern in all the Asian stock indices, but also demonstrates the risk of drawing the wrong inferences on mean reversion when the ADF test is applied to data governed by nonlinearity.

Testing the Assertion that Emerging Asian Stock Markets are Becoming More Efficient

Testing the assertion that emerging stock markets are becoming more efficient over time has received increasing attention in the empirical literature in recent years. However, the statistical tests adopted in extant literature are designed to detect linear predictability, and hence disregard the possible existence of nonlinear predictability. Motivated by this concern, this study computes the bicorrelation statistics of Hinich (1996) in fixed-length moving sub-sample windows, and found that nonlinear predictability for all returns series follows an evolutionary time path. However, for most indices with the exception of Taiwan SE Weighted, there is no clear trend towards higher efficiency as predicted by the classical EMH.