Predicting Volatility in the Foreign Exchange Market



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    • Jorion is from the Graduate School of Management, University of California at Irvine. Thanks are due to David Bates, Hendrik Bessembinder, Michael Brennan, Stephen Figlewski, Steven Heston, two referees, and seminar participants at UC-Irvine, UCLA, Georgetown University, the Université Libre de Bruxelles, the University of Maryland, the University of Wisconsin-Madison, and the Cornell conference on derivatives for useful comments. I am also grateful to the Institute for Quantitative Research in Finance for financial support.


Measures of volatility implied in option prices are widely believed to be the best available volatility forecasts. In this article, we examine the information content and predictive power of implied standard deviations (ISDs) derived from Chicago Mercantile Exchange options on foreign currency futures. The article finds that statistical time-series models, even when given the advantage of “ex post” parameter estimates, are outperformed by ISDs. ISDs, however, also appear to be biased volatility forecasts. Using simulations to investigate the robustness of these results, the article finds that measurement errors and statistical problems can substantially distort inferences. Even accounting for these, however, ISDs appear to be too variable relative to future volatility.