Long memory properties and asymmetric effects of emerging equity market: Evidence from Malaysia

Purpose - The purpose of this paper is to examine the long memory property of equity returns and volatility of emerging equity market by focusing on the Malaysian equity market, namely the Kuala Lumpur Stock Exchange (KLSE). Design/methodology/approach - The study adopts the Fractionally Integrated GARCH (FIGARCH) model and Fractionally Integrated Asymmetric Power ARCH (FIAPARCH), focusing on the Malaysian data covering the period from April 15, 2004 to April 30, 2007. Findings - The study finds evidence of long memory property as well as asymmetric effects in the volatility of the KLSE. The traditional ARCH/GARCH is shown to be insufficient in modeling the volatility persistence. The FIAPARCH specification outperforms the FIGARCH model by capturing both asymmetry effects and long memory in the conditional variance. Research limitations/implications - The results of this study have practical implications for the investors intending to invest in the emerging markets such as Malaysia. Understanding volatility and developing the appropriate models are important since volatility can be a measure of risk which is highly relevant in forecasting the conditional volatility of returns for portfolio selection, asset pricing, and value at risk, option pricing and hedging strategies. Originality/value - This study contributes in providing the empirical evidence on the long memory property of equity returns and volatility of an emerging equity market with reliable estimation models, which is currently lacking, particularly for emerging markets.

[1]  R. Kili.  On the long memory properties of emerging capital markets: evidence from Istanbul stock exchange , 2004 .

[2]  Sébastien Laurent,et al.  G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH Models , 2001 .

[3]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[4]  B. Mandelbrot.  When Can Price Be Arbitraged Efficiently? A Limit to the Validity of the Random Walk and Martingale Models , 1971 .

[5]  A. Lo,et al.  When are Contrarian Profits Due to Stock Market Overreaction? , 1989 .

[6]  Tim Bollerslev,et al.  Quasi-maximum likelihood estimation of dynamic models with time varying covariances , 1988 .

[7]  R. Engle,et al.  Time-Varying Volatility and the Dynamic Behavior of the Term Structure , 1991 .

[8]  R. Engle.  Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[9]  T. Bollerslev,et al.  MODELING AND PRICING LONG- MEMORY IN STOCK MARKET VOLATILITY , 1996 .

[10]  Yoshihiro Yajima,et al.  ON ESTIMATION OF LONG-MEMORY TIME SERIES MODELS , 1985 .

[11]  Daniel B. Nelson.  CONDITIONAL HETEROSKEDASTICITY IN ASSET RETURNS: A NEW APPROACH , 1991 .

[12]  Yiu Kuen Tse,et al.  The conditional heteroscedasticity of the yen-dollar exchange rate , 1998 .

[13]  M. T. Greene,et al.  Long-term dependence in common stock returns , 1977 .

[14]  Francis X. Dieobold.  Modeling The persistence Of Conditional Variances: A Comment , 1986 .

[15]  N. Crato.  Some international evidence regarding the stochastic memory of stock returns , 1994 .

[16]  W. Andrew.  LO, . Long-Term Memory in Stock Market Prices, Econometrica, , . , 1991 .

[17]  G. Booth,et al.  Are There Long Cycles in Common Stock Returns , 1988 .

[18]  Christopher F. Baum,et al.  Long memory in the Greek stock market , 1997 .

[19]  Ignacio N. Lobato,et al.  Real and Spurious Long-Memory Properties of Stock-Market Data , 1996 .

[20]  H. E. Hurst,et al.  Long-Term Storage Capacity of Reservoirs , 1951 .

[21]  J. Geweke,et al.  THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS , 1983 .

[22]  Fallaw Sowell.  Maximum likelihood estimation of stationary univariate fractionally integrated time series models , 1992 .

[23]  Campbell R. Harvey,et al.  PREDICTABLE RISK AND RETURNS IN EMERGING MARKETS , 1999 .

[24]  Jussi Tolvi,et al.  Modeling Financial Time Series with S‐Plus , 2003 .

[25]  J. Wooldridge,et al.  Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances , 1992 .

[26]  Bruce E. Hansen,et al.  Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator , 1994, Econometric Theory.

[27]  Richard T. Baillie,et al.  Further Long Memory Properties of Inflationary Shocks , 2002 .

[28]  A. Lo.  Long-Term Memory in Stock Market Prices , 1989 .

[29]  R. Baillie,et al.  Fractionally integrated generalized autoregressive conditional heteroskedasticity , 1996 .

[30]  Y. Tse,et al.  Residual-Based Diagnostics for Conditional Heteroscedasticity Models , 2002 .

[31]  Ying-Wong Cheung,et al.  A search for long memory in international stock market returns , 1995 .

[32]  C. Granger,et al.  A long memory property of stock market returns and a new model , 1993 .