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Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data

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  • CORNELIS A. LOS

    (Kent State University)

Abstract

The efficiency of speculative markets, as represented by Fama's 1970 fair game model, is tested on weekly price index data of six Asian stock markets - Hong Kong, Indonesia, Malaysia, Singapore, Taiwan and Thailand - using Sherry's (1992) non-parametric methods. These scientific testing methods were originally developed to analyze the information processing efficiency of nervous systems. In particular, the stationarity and independence of the price innovations are tested over ten years, from June 1986 to July 1996. These tests clearly show that all six stock markets lacked at least one of the two required fair game attributes, and, accordingly, Fama's Efficient Market Hypothesis must be rejected for these Asian markets. However, Singapore emerged from these tests as the most efficient regional Asian stock market. A tentative ranking in order of stock market efficiency is: Singapore, Thailand, Indonesia, Malaysia, Hong Kong and Taiwan. Singapore's stock market pricing is closest to the speculative market behavior which can support stock options. Our tests show both Hong Kong and Taiwan to be inefficient markets. Both exhibit non-stationary (likely because of continuing institutional changes) and dependent price innovations, making them particularly unsuitable for stock option pricing. In Taiwan the weekly price innovations show even higher order (Markov) dependencies. Although the price innovations in Malaysia, Thailand and Indonesia are at least stationary at the weekly level, they exhibit regular higher-order transitions and the large sustained movements in both bull and bear markets, which are so characteristic for illiquid emerging markets. All six Asian stock markets exhibit strong price trend behavior, which, perhaps, can be profitably exploited by technical analysis with first- order Markov filters (e.g., Kalman filters) in windows of between a week and more than a month.

Suggested Citation

  • Cornelis A. Los, 2004. "Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data," Finance 0409033, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0409033
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    1. Myung Jig Kim & Charles R. Nelson & Richard Startz, 1991. "Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 515-528.
    2. Los, Cornelis A., 1998. "Optimal multi-currency investment strategies with exact attribution in three Asian countries," Journal of Multinational Financial Management, Elsevier, vol. 8(2-3), pages 169-198, September.
    3. Poterba, James M & Summers, Lawrence H, 1986. "The Persistence of Volatility and Stock Market Fluctuations," American Economic Review, American Economic Association, vol. 76(5), pages 1142-1151, December.
    4. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    5. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    6. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    7. N. Gregory Mankiw & David Romer & Matthew D. Shapiro, 1991. "Stock Market Forecastability and Volatility: A Statistical Appraisal," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 455-477.
    8. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    9. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    10. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    11. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    12. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    13. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    14. Pagan, Adrian R. & Schwert, G. William, 1990. "Testing for covariance stationarity in stock market data," Economics Letters, Elsevier, vol. 33(2), pages 165-170, June.
    15. David H. Cutler & James M. Poterba & Lawrence H. Summers, 1988. "What Moves Stock Prices?," Working papers 487, Massachusetts Institute of Technology (MIT), Department of Economics.
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    Cited by:

    1. Jeyanthi Karuppiah & Cornelis A. Los, 2000. "Wavelet Multiresolution Analysis of High-Frequency FX Rates, Summer 1997," School of Economics and Public Policy Working Papers 2000-06, University of Adelaide, School of Economics and Public Policy.
    2. Cornelis A. Los, 2005. "Measurement of Financial Risk Persistence," Finance 0502013, University Library of Munich, Germany.
    3. Karuppiah, Jeyanthi & Los, Cornelis A., 2005. "Wavelet multiresolution analysis of high-frequency Asian FX rates, Summer 1997," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 211-246.
    4. Cornelis A. Los, 2004. "The Changing Concept of Financial Risk," Finance 0409034, University Library of Munich, Germany.

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    More about this item

    Keywords

    Nonparametrics; Efficiency; Stock Markets;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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