Ranking market efficiency for stock markets: A nonlinear perspective

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.

[1]  E. Fama.  EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[2]  A. Lo,et al.  THE ECONOMETRICS OF FINANCIAL MARKETS , 1996, Macroeconomic Dynamics.

[3]  A. Lo,et al.  Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis , 2005 .

[4]  K. Lim,et al.  Financial crisis and stock market efficiency: Empirical evidence from Asian countries , 2008 .

[5]  Sanford J. Grossman.  On the Impossibility of Informationally Efficient Markets , 1980 .

[6]  M. Hinich,et al.  Events that Shook the Market: An Insight from Nonlinear Serial Dependencies in Intraday Returns , 2006 .

[7]  C. Granger,et al.  An introduction to bilinear time series models , 1979 .

[8]  M. Hinich,et al.  Testing the Assertion that Emerging Asian Stock Markets are Becoming More Efficient , 2006 .

[9]  B. M. Tabak,et al.  Evidence of long range dependence in Asian equity markets: the role of liquidity and market restrictions , 2004 .

[10]  A. Lo.  The Adaptive Markets Hypothesis , 2004 .

[11]  Samir Saadi,et al.  On the validity of conventional statistical tests given evidence of non-synchronous trading and non-linear dynamics in returns generating process , 2006 .

[12]  J. Binner,et al.  Money, measurement and computation , 2006 .

[13]  N. Johnson,et al.  Financial market complexity , 2003 .

[14]  B. M. Tabak,et al.  Ranking efficiency for emerging markets , 2004 .

[15]  M. Hinich.  Testing for dependence in the input to a linear time series model , 1996 .