Volatility Forecasting in the Hang Seng Index using the GARCH Approach

Asia-Pacific Financial Markets volume 16, pages51–63(2009)Cite this article

Abstract

The aim of this paper is to add to the literature on volatility forecasting using data from the Hong Kong stock market to determine if forecasts from GARCH based models can outperform simple historical averaging models. Overall, unlike previous studies we find that the GARCH models with non-Normal distributions show a robust volatility forecasting performance in comparison to the historical models. The results indicate that although not all models outperform simple historical averaging, the EGARCH based models, with non-normal conditional volatility, tend to produce more accurate out-of-sample forecasts using both standard measures of forecast accuracy and financial loss functions. In addition we test for asymmetric adjustment in the Hang Seng, finding strong evidence of asymmetries due to the domination of financial and property firms in this market.

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Affiliations

  1. Department of Economics and International Development, University of Bath, Bath, UK

    Wei Liu & Bruce Morley

Authors
  1. Wei Liu
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  2. Bruce Morley
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Correspondence to Bruce Morley.

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Liu, W., Morley, B. Volatility Forecasting in the Hang Seng Index using the GARCH Approach. Asia-Pac Financ Markets 16, 51–63 (2009). https://doi.org/10.1007/s10690-009-9086-4

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Keywords

  • GARCH
  • Hang Seng
  • Volatility
  • Forecast
  • Asymmetric
  • Stock price