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A Mixed Historical Formula to forecast volatility

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  • Roberto Ferulano

    (Finance and Statistics, University of Perugia)

Abstract

This study presents a new methodology for forecasting volatility. It relies on a weighted mean of short and long estimates of variance, based on a Moving Average framework. The quality of the predictions obtained with the proposed formula was checked with both simulated and real data. When applied to the analysis of simulated data, the new formula provides the least reliable forecast when a Random Walk is used as Data Generating Process (DGP) and the forecast variance is a simple Moving Average. This is also the case when the DGP belongs to the ARCH model family and the associated forecast formula is used. However, compared to existing approaches, the new methodology allows for the most reliable forecast on 5-day and 20-day horizons, when it is applied to Index, Fixed Income and Foreign Exchange data series.

Suggested Citation

  • Roberto Ferulano, 2009. "A Mixed Historical Formula to forecast volatility," Journal of Asset Management, Palgrave Macmillan, vol. 10(2), pages 124-136, June.
    • Handle: RePEc:pal:assmgt:v:10:y:2009:i:2:d:10.1057_jam.2009.2
    DOI: 10.1057/jam.2009.2
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    References listed on IDEAS

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    Cited by:

    1. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
    2. Moawia Alghalith, 2012. "New methods of estimating volatility and returns," Journal of Asset Management, Palgrave Macmillan, vol. 13(1), pages 1-4, February.
    3. Alghalith, Moawia, 2010. "New methods of estimating stochastic volatility and the stock return," MPRA Paper 20303, University Library of Munich, Germany.

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