Research Article Open Access

A Generalized Discrete-Time Long Memory Volatility Model for Financial Stock Exchange

Chin Wen Cheong

Abstract

We proposed a simple way to combine a few long memory models in financial market volatility modeling using daily, range and high frequency data. This model was able to fit the return, range of daily return or realized volatility under a parametric heavy-tailed distribution. Model was flexible to include additional volatility information as the contemporaneous variables. Empirical results found that the proposed model provides substantial improvement in the model fitting, specification and most importantly, a better out-of sample forecasting in the Malaysian stock market.

American Journal of Applied Sciences
Volume 4 No. 12, 2007, 970-976

DOI: https://doi.org/10.3844/ajassp.2007.970.976

Submitted On: 25 April 2007 Published On: 31 December 2007

How to Cite: Cheong, C. W. (2007). A Generalized Discrete-Time Long Memory Volatility Model for Financial Stock Exchange. American Journal of Applied Sciences, 4(12), 970-976. https://doi.org/10.3844/ajassp.2007.970.976

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Keywords

  • realized volatility
  • fractionally integrated
  • autoregressive conditional heteroscedastic (ARCH)