Nonlinear serial dependence and the weak-form efficiency of Asian emerging stock markets

Lim, Kian−Ping; Brooks, Robert Darren; Hinich, Melvin J.

doi:10.1016/j.intfin.2007.08.001

Cited by 65 publications

(38 citation statements)

References 29 publications

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“…Bianco and Renò (2006) found negative serial correlation in the returns of Italian stock index futures for periods smaller than 20 minutes. Lim et al (2008) examined ten Asian emerging stock markets and discovered that all the returns series exhibit non-linear serial dependence. Serletis and Rosenberg (2009) analysed daily data on four US stock market indices and concluded that US stock market returns display mean reversion.…”

Section: Autocorrelationmentioning

confidence: 99%

The Efficient Market Hypothesis: Empirical Evidence

Sewell¹

2012

IJSP

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The efficient market hypothesis (EMH) has been the central proposition of finance since the early 1970s and is one of the most well-studied hypotheses in all the social sciences, yet, surprisingly, there is still no consensus, even among financial economists, as to whether the EMH holds. Five statistical analyses are conducted in an attempt to explicate such apparently contrary convictions. An analysis of daily, weekly, monthly and annual Dow Jones Industrial Average log returns found that first-order autocorrelation is small but positive for all time periods, with the autocorrelations for daily and weekly returns closest to zero, and thus an efficient market. A standard runs test showed that the hypothesis of independence is strongly rejected for daily returns, but accepted for weekly, monthly and annual returns, whilst the results of a more sophisticated runs test showed that daily, weekly and decreasing returns are the least consistent with an efficient market. Rescaled range analysis was conducted on the same data sets, and there was no significant evidence for the existence of long memory in the returns, a result consistent with market efficiency. Finally, from an analysis of investment newsletters it may be concluded that technical analysisas applied by practitioners-fails to outperform the market. I reconcile the fact that daily stock market log returns pass linear statistical tests of efficiency, yet non-linear forecasting methods can still generate above-average riskadjusted returns, whilst discretionary technical analysts fail to make abnormal returns.

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Section: Autocorrelationmentioning

confidence: 99%

The Efficient Market Hypothesis: Empirical Evidence

Sewell¹

2012

IJSP

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“…On the other hand, a large number of others studies find that stock market indexes are generally characterized by long lasting pure noise processes followed by short-lived nonlinear dependence. Lim et al (2008) report similar stock market characteristic for ten Asian emerging markets. The study by Bonilla et al (2006) also shows that equities in Latin America exhibit the pure noise processes, which last for a long period of time, and are followed by nonlinear dependence of a shorter duration.…”

Section: Literature Reviewmentioning

confidence: 76%

A Study of Nonlinear Dynamics in Equity Market Index: Evidence from Turkey

Jirasakuldech

Emekter

2016

berj

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“…Chauvet and Collier (2008) in their study concluded that the political party in power always lure the voters by offering benefits and election centric reforms in the preelection period to attract more votes. In an empirical study by Lim et al (2008), documented that general elections and other important political events have a short-term impacts on stock markets. Sathyanarayana and Pushpa B. V. (2016) tried to investigate the impact of Brexit referendum on global stock markets found a significant impact only on European stock markets and not on Asian and American stock markets.…”

Section: Literature Reviewmentioning

confidence: 99%