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Volatility forecasts: the role of asymmetric and long-memory dynamics and regional evidence

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  • Twm Evans
  • David McMillan

Abstract

This article seeks to examine the forecasting performance of nine competing models for daily volatility for stock market returns of 33 economies. Whilst volatility is an important variable in many financial applications including those relating to areas of risk management there exits little consensus with regard to the most appropriate model. The results of this article seek to bring some closure to the debate. Our results suggest that in 70% of our cases the GARCH-class of model provide the best forecasts and in particular models that account for either asymmetry or long-memory dynamics. Outwith the GARCH-class, the moving average model provides reasonable forecasts.

Suggested Citation

  • Twm Evans & David McMillan, 2007. "Volatility forecasts: the role of asymmetric and long-memory dynamics and regional evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 17(17), pages 1421-1430.
    • Handle: RePEc:taf:apfiec:v:17:y:2007:i:17:p:1421-1430
    DOI: 10.1080/09603100601007149
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    3. Wamg, Jianxin, 2011. "Forecasting Volatility in Asian Stock Markets: Contributions of Local, Regional, and Global Factors," Asian Development Review, Asian Development Bank, vol. 28(2), pages 32-57.
    4. David McMillan & Raquel Quiroga Garcia, 2009. "Intra-day volatility forecasts," Applied Financial Economics, Taylor & Francis Journals, vol. 19(8), pages 611-623.
    5. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    6. Liu, Hung-Chun & Chiang, Shu-Mei & Cheng, Nick Ying-Pin, 2012. "Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 78-91.
    7. Tanuj Nandan & Puja Agrawal, 2016. "Pricing Efficiency in CNX Nifty Index Options Using the Black–Scholes Model: A Comparative Study of Alternate Volatility Measures," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 10(2), pages 281-304, May.

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