Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models |
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| Affiliation: | 1. School of Finance, Yunnan University of Finance and Economics, Kunming, China;2. School of Economics and Management, Southwest Jiaotong University, Chengdu, China;3. School of Economics & Management, Panzhihua University, Sichuan, China;4. School of Business, Sichuan Normal University, Chengdu, China;1. School of Economics and Management, Southwest Jiaotong University, Chengdu, China;2. Department of Applied Finance, Macquarie University, Sydney, Australia;3. Service Science and Innovation Key Laboratory of Sichuan Province, China |
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| Abstract: | We compare forecasts of the realized volatility of the pound, mark and yen exchange rates against the dollar, calculated from intraday rates, over horizons ranging from one day to three months. Our forecasts are obtained from a short memory ARMA model, a long memory ARFIMA model, a GARCH model and option implied volatilities. We find intraday rates provide the most accurate forecasts for the one-day and one-week forecast horizons while implied volatilities are at least as accurate as the historical forecasts for the one-month and three-month horizons. The superior accuracy of the historical forecasts, relative to implied volatilities, comes from the use of high frequency returns, and not from a long memory specification. We find significant incremental information in historical forecasts, beyond the implied volatility information, for forecast horizons up to one week. |
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