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Longer-Term Time-Series Volatility Forecasts


  • Ederington, Louis H.
  • Guan, Wei


Option pricing models and longer-term value-at-risk (VaR) models generally require volatility forecasts over horizons considerably longer than the data frequency. The typical recursive procedure for generating longer-term forecasts keeps the relative weights of recent and older observations the same for all forecast horizons. In contrast, we find that older observations are relatively more important in forecasting at longer horizons. We find that the Ederington and Guan (2005) model and a modified EGARCH (exponential generalized autoregressive conditional heteroskedastic) model in which parameter values vary with the forecast horizon forecast better out-of-sample than the GARCH (generalized autoregressive conditional heteroskedastic), EGARCH, and Glosten, Jagannathan, and Runkle (GJR) models across a wide variety of markets and forecast horizons.

Suggested Citation

  • Ederington, Louis H. & Guan, Wei, 2010. "Longer-Term Time-Series Volatility Forecasts," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(04), pages 1055-1076, August.
  • Handle: RePEc:cup:jfinqa:v:45:y:2010:i:04:p:1055-1076_00

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    Cited by:

    1. Jordan French, 2016. "Back to the Future Betas: Empirical Asset Pricing of US and Southeast Asian Markets," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 4(3), pages 1-13, July.
    2. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
    3. Ederington, Louis H. & Guan, Wei, 2010. "How asymmetric is U.S. stock market volatility?," Journal of Financial Markets, Elsevier, vol. 13(2), pages 225-248, May.
    4. repec:wsi:rpbfmp:v:15:y:2012:i:01:n:s0219091511500032 is not listed on IDEAS
    5. Vogel, Harold L. & Werner, Richard A., 2015. "An analytical review of volatility metrics for bubbles and crashes," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 15-28.

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