Stock Returns Predictability and the Adaptive Market Hypothesis: Evidence from India

Hiremath, Gourishankar S and Kumari, Jyoti (2013): Stock Returns Predictability and the Adaptive Market Hypothesis: Evidence from India.

Abstract

The present paper evaluates whether the adaptive market hypothesis provides a better description of the behavior of Indian stock market using daily values of Sensex and Nifty, the two major indices of India from January 1991 to April 2013. We employed linear and nonlinear methods to evaluate the hypothesis empirically. The linear tests show a cyclical pattern in linear dependence suggesting that the Indian stock market switched between periods of efficiency and inefficiency. However, the results from nonlinear tests reveal a strong evidence of nonlinearity in returns throughout the sample period with a sign of the taping magnitude of nonlinear dependence in the recent period. The findings suggest that Indian stock market is still in the first stage of AMH and hence calls for an active portfolio management for excess returns.

• Item Type: MPRA Paper
• Language: English
• Keywords: Adaptive market hypothesis, Market efficiency, Random walk, Autocorrelation, Nonlinearity, Predictability, behavioral finance
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; G - Financial Economics > G0 - General > G02 - Behavioral Finance: Underlying Principles; G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates; G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading

References

Alvarez-Ramirez, J., Rodriguez E., & Espinosa-Paredes, G. (2012). Is the US stock market becoming weakly efficient over time? Evidence from 80-year-long data. Physica, A 391, 5643-5647.

Amanulla, S., & Kamaiah, B. (1998). Indian stock market: Is it informationally efficient? Prajnan, 25, 473-485.

Bachelier, L. (1900). Theory of Speculation. PhD Thesis, Faculty of the Academy of Paris.

Barua, S. K. (1981). The short run price behaviour of securities: Some evidence on efficiency of Indian capital market. Vikalpa, 16, 93-100.

Brock, W. A., Sheinkman, J.A., Dechert, W.D., & LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Review, 15,197–235.

Campbell, J.Y., Lo, A.W., & MacKinlay, A.C. (1997). The Econometrics of financial markets. New Jersey: Princeton University Press.

Charles, A., Darne, O., & Kim, H. (2012). Exchange-rate predictability and adaptive market hypothesis: Evidence from major exchange rates. Journal of International Money and Finance, 31, 1607-1626.

Chow, K.V., & Denning, K.C. (1993). A simple multiple variance ratios test. Journal of Econometrics, 58, 385-401.

Engle, R.F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50, 987-1007.

Fama, E.F. (1970). Efficient capital markets: A review of theory and empirical work. Journal of Finance, 25, 383-417.

Granger, C.W.J., & Anderson, A.P. (1978). An introduction to bilinear time series models. Gottingen: V & R

Grassberger, P., & Procaccia, I. (1983). Characterization of strange attractors. Physical Review Letters 50, 346-340.

Hsieh, D.A. (1989). Testing for nonlinear dependence in daily foreign exchange rates. The Journal of Business, 62 (3), 339-368.

Hinich, M.J. (1996). Testing for dependence in the input to a linear time series model. Journal of Nonparametric Statistics, 6, 205-221.

Ito, M., & Sugiyama, S. (2009). Measuring the degree of time varying market inefficiency. Economics Letters, 103, 62–64.

Jarque, C.M., Bera, A.K. 1980. Efficient test of normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6, 255-259.

Kim, J.H., Shamsuddin, A., & Lim, K.P. (2011). Stock returns predictability and the adaptive markets hypothesis. Evidence from century long U.S. data. Journal of Empirical Finance, 188, 68-879.

Ljung, G.M., & Box, G.E.P. (1978). On a measure of lack of fit in time series models. Biometrika, 65, 297-303.

Lo, A.W. (2004). The adaptive markets hypothesis: market efficiency from an evolutionary perspective. Journal of Portfolio Management, 30, 15–29.

Lo, A.W. (2005). Reconciling efficient markets with behavioral finance: The adaptive markets hypothesis. The Journal of Investment Consulting, 7, 21–44.

Lo, A.W., & MacKinlay, A.C. (1988). Stock market prices do not follow random walks: Evidence from a simple specification test. Review of Financial Studies, 1, 41-66.

Lo, A.W., & MacKinlay, A.C. (1999). A non-random walk down Wall Street. New Jersey: Princeton University Press.

Malkiel, B.G. (1973). A random walk down Wall Street. New York: W. W. Norton & Co.

McLeod, A.I., & Li, W.K. (1983). Diagnostic checking ARMA time series models using squared-residual autocorrelations. Journal of Time Series Analysis, 4, 269-273.

Noda, A. (2012, August). A test of the adaptive market hypothesis using non-Bayesian time-varying AR model in Japan. http://arxiv.org. Accessed on 25 April 2013.

Poshakwale, S. (2002). The random walk hypothesis in the emerging Indian stock market. Journal of Business Finance & Accounting, 29, 1275-1299.

Rao, K.N., & Mukherjee, K. (1971). Random walk hypothesis: An empirical study. Arthaniti, 14, 53-58.

Samuelson, P. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6, 41-49.

Sharma, J.L., & Kennedy, R.E. (1977). A comparative analysis of stock price behavior on the Bombay, London, and New York stock exchanges. The Journal of Financial and Quantitative Analysis, 12, 391-413.

Standard and Poor’s. (2013). Global stock market Fact book. New York

Tsay, R.S. (1986). Nonlinearity tests for time series. Biometrika, 73, 461-466.

Taylor, S.J. (2005). Asset price dynamics, volatility, and prediction. New Jersey: Princeton University Press

Urquhart, A., & Hudson, R. (2013). Efficient or adaptive markets? Evidence from major stock markets using very long historic data. International Review of Financial Analysis, 28,130-142.