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Forecasting exchange rate volatility: a multiple horizon comparison using historical, realized and implied volatility measures

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  • David T. L. Siu

    (Department of Accounting & Finance, Monash University, Melbourne, Australia)

  • John Okunev

    (Global Alpha Portfolio Management Pty Ltd)

Abstract

Recent studies suggest realized volatility provides forecasts that are as good as option-implied volatilities, with improvement stemming from the use of high-frequency data instead of a long-memory specification. This paper examines whether volatility persistence can be captured by a longer dataset consisting of over 15 years of intra-day data. Volatility forecasts are evaluated using four exchange rates (AUD|USD, EUR|USD, GBP|USD, USD|JPY) over horizons ranging from 1 day to 3 months, using an expanded set of short-range and long-range dependence models. The empirical results provide additional evidence that significant incremental information is found in historical forecasts, beyond the implied volatility information for all forecast horizons. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • David T. L. Siu & John Okunev, 2009. "Forecasting exchange rate volatility: a multiple horizon comparison using historical, realized and implied volatility measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 465-486.
    • Handle: RePEc:jof:jforec:v:28:y:2009:i:6:p:465-486
    DOI: 10.1002/for.1090
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    1. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.

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