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.

Given the growing empirical evidence that returns predictability follows an evolutionary path, it calls into question not only the usefulness of conventional statistical tests of market efficiency as highlighted by Saadi et al. (2006), but also the adequacy of the efficient markets hypothesis to explain observed market dynamics.

This study finds that there is a common force which brings all the five ASEAN stock markets together in the long run by the nonparametric tests. This suggests that shocks from any of these five markets may spillover to the other markets in the same region. The recent Asian financial crisis bears a good testimony to this ‘contagion effect’. Subsequently, there would be no long run gain from international portfolio diversification. Specifically, investors with long run horizons may not benefit from an investment made across the countries in this ASEAN region. One possible explanation for this intra-ASEAN stock markets integration is their strong economic ties, especially intra-ASEAN trade and investment that has indirectly linked their stock indices.

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The literature on weak-form efficient market hypothesis (EMH) has experienced a phenomenal growth over the past few decades, with the empirical framework mostly directed towards testing the absolute version of market efficiency. Evans (2006) represents a small amount of studies that addressed the relative efficiency of financial markets. The present paper discusses the limitations of absolute market efficiency and surveys some measures proposed for assessing relative efficiency in extant literature.

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.

This paper revisits the income convergence hypothesis by using the nonlinear unit root test of Kapetanios et al. [Kapetanios, G., Shin, Y. and A. Snell, 2003. Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics 112, 359–379.]. Out of the 12 OECD income gaps in which nonlinearity has been detected, two cases of long-run converging and four cases of catching up are found.

The present study adopts the framework of Lim et al. (2006) who conjectured that the existence of nonlinear serial dependencies is due to shocks that unsettled the market and caused large deviations from equilibrium. Specifically, this article extends the investigation to shed further light on whether different economic sectors of the Malaysian stock market are subjected to the same shocks effects. The results reveal that the Russian crisis, negative economic outlook, unorthodox capital control measures, increased political tension, uncertainty over Central Limit Order Book issue, and the imposition of repatriation levy, have sent shock waves throughout the domestic stock market.

The objective of this paper is to re-examine the weak-form efficiency of 10 Asian emerging stock markets. Using a battery of nonlinearity tests, the statistical results reveal that all the returns series still contain predictable nonlinearities even after removing linear serial correlation from the data. The next stage of sub-sample analysis using the Hinich [Hinich, M., 1996. Testing for dependence in the input to a linear time series model. Journal of Nonparametric Statistics 6, 205–221] bicorrelation test shows that the 10 Asian series follow a pure noise process for long periods of time, only to be interspersed with brief periods of strong nonlinear dependence. The exploratory investigation found that the cross-country differences in nonlinear departure from market efficiency can be explained by market size and trading activity, while the transient burst of nonlinear periods in each individual market can be attributed largely to the occurrence of economic and political events.

The present paper demonstrates, via a rolling sample approach, that the stylized fact of nonlinear dependence in stock returns is quite localized in time, suggesting that market efficiency evolves over time. Given that the rolling sample framework is able to detect periods of efficiency/inefficiency, the relative efficiency of stock markets can easily be assessed by comparing the total time windows these markets exhibit significant nonlinear serial dependence. It was found that the US market is the most efficient while Argentine is at the end of the ranking.

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.

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.

This paper advocates a reverse from of event studies that is data−dependent to determine endogeneously the events that trigger non−linear market behavior. Using the Malaysian stock market as our case study, coupled with the ‘windowing’ approach proposed by Hinich and Patterson (1995), the present study is able to identify major political and economic events that contributed to the short bursts of non−linear behavior. The present framework can be extended to individual firm to examine the adjustment of its stock price to firm−specific events, which will provide deeper insight into issues on corporate finance.

This study examines the issue of income convergence in the East−Asian economies from the non−linear point of view. It is shown in this study that the income gaps between Japan and the rest of the East−Asian economies exhibit nonlinearities. It is further shown that after taking non−linearity into consideration, China, Indonesia, Malaysia, Thailand and the Philippines exhibit divergence behaviour with respect to Japan’s income, whereas Hong Kong, Korea, Taiwan and Singapore show otherwise.

The objective of this study is to empirically examine the income disparity between Japan and each of the five major economies of South East Asia (ASEAN−5) during the period of 1960 to 1997, utilizing the popular augmented Dickey−Fuller (ADF) unit root test. The results provide evidence of income divergence between Japan and each of the ASEAN−5 economies. To avoid the problem associated with structural break, this study proceeds with the jointly crash and changes in trend model proposed by Zivot and Andrews (1992), and is able to obtain evidence of long run income convergence between the Japanese and Singaporean economies. As for the rest of the four ASEAN countries− Indonesia, Malaysia, the Philippines and Thailand, the earlier results of income divergence remain valid and hence suggest that it would be a more realistic and urgent goal to narrow the income gap among these five core economies of ASEAN.

The finding of exchange rate–relative price nonlinear cointegration relationship in Malaysia, among others, suggests that nonlinear Purchasing Power Parity (PPP) equilibrium may be regarded as reference point in judging the short run misalignment of the Ringgit currency and thereby deducing effective policy actions. Moreover, economists who wish to extend the simple PPP exchange rate model into the more complicated monetary exchange models may do so comfortably, at least in the text of Malaysia. Nonetheless, such attempt should be tailored in a nonlinear way to suit the nonlinear characteristic of exchange rate behaviour.

This study utilizes the Hinich portmanteau bicorrelation test in conjunction with the windowed testing procedure to examine the cross−temporal universality of non−linear dependencies in the returns series for Asian stock market indices. As a whole, the detected non−linear dependencies do not appear to be persistent or stable across time for all the stock markets. In particular, the underlying process is of a switching type, with the pure noise process from time to time switches to a non−linear dependent stochastic process for some unknown length of time, and then switches back to pure−noise. This provides a plausible explanation for the disappointing forecasting performance of many non−linear models, as these existing models do not take note of the episodic transient nature of the non−linear dependency structures.

This study re-examines the validity of the relationship between the Singapore dollar–U.S. dollar exchange rate and relative prices using the latest econometric methodologies that account for non-linearity. Among others, this study finds Exponential Smooth Transition Autoregressive (ESTAR)-type non-linear mean-reverting adjustment process of the nominal Singapore dollar–U.S. dollar rate towards the consumer price index ratio. Unlike previous findings of a linear cointegration relationship between the nominal Singapore dollar–U.S. dollar exchange rate and consumer price index ratio, this study shows that the relationship is in fact non-linear in nature. The major economic implications of our findings are: (1) policy makers need to take non-linearity into consideration in their policy decisions; (2) the Monetary Authority of Singapore (MAS) is able to maintain the macroeconomic equilibrium despite the authority’s strong dollar policy; and (3) one should keep track of Singapore’s monetary policy and other innovations in aggregate demand in order to closely monitor the movement of the Singapore exchange rate.

Utilizing the formal linearity test of Luukkonen, Saikkonen and Teräsvirta (Biometrika, 75, 491-499, 1998) as diagnostic tool, the empirical finding suggests that the linear autoregressive (AR) model is inadequate in describing the real exchange rates behaviour of 11 Asian economies. It is noted that the conventional battery of diagnostic tests is capable of identifying the inadequacy of the linear model in only three of these series. Moreover, the linearity nature of this behaviour has been formally rejected in favour of the non-linear smooth transition autoregressive (STAR) model. The finding of non-linearity in the data generating process of these real exchange rates warrants that the use of linear framework in empirical modelling and statistical testing procedures in the field of exchange rates may lead to an inappropriate policy conclusions.