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題名 A Comparison of Seasonal Adjustment Methods When Forecasting Intraday Volatility
作者 張元晨
Martens, Martin ; Chang, Yuan-Chen ; Taylor, Stephen J.
貢獻者 財管系
日期 2002.06
上傳時間 30-May-2014 17:48:50 (UTC+8)
摘要 In this article we compare volatility forecasts over a thirty-minute horizon for the spot exchange rates of the Deutsche mark and the Japanese yen against the U.S. dollar. Explicitly modeling the intraday seasonal pattern improves the out-of-sample forecasting performance. We find that a seasonal estimated from the log of squared returns improves with the use of simple squared returns, and that the flexible Fourier form (FFF) is an efficient way of determining the seasonal. The two-step approach that first estimates the seasonal using the FFF and then the parameters of the generalized autoregressive conditional heteroskedasticity (GARCH) model for the deseasonalized returns performs only marginally worse than the computationally expensive periodic GARCH model that includes the FFF.
關聯 Journal of Financial Research, 25(2), 283-299
資料類型 article
dc.contributor 財管系en_US
dc.creator (作者) 張元晨zh_TW
dc.creator (作者) Martens, Martin ; Chang, Yuan-Chen ; Taylor, Stephen J.en_US
dc.date (日期) 2002.06en_US
dc.date.accessioned 30-May-2014 17:48:50 (UTC+8)-
dc.date.available 30-May-2014 17:48:50 (UTC+8)-
dc.date.issued (上傳時間) 30-May-2014 17:48:50 (UTC+8)-
dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=74725-
dc.description.abstract (摘要) In this article we compare volatility forecasts over a thirty-minute horizon for the spot exchange rates of the Deutsche mark and the Japanese yen against the U.S. dollar. Explicitly modeling the intraday seasonal pattern improves the out-of-sample forecasting performance. We find that a seasonal estimated from the log of squared returns improves with the use of simple squared returns, and that the flexible Fourier form (FFF) is an efficient way of determining the seasonal. The two-step approach that first estimates the seasonal using the FFF and then the parameters of the generalized autoregressive conditional heteroskedasticity (GARCH) model for the deseasonalized returns performs only marginally worse than the computationally expensive periodic GARCH model that includes the FFF.en_US
dc.language.iso en_US-
dc.relation (關聯) Journal of Financial Research, 25(2), 283-299en_US
dc.title (題名) A Comparison of Seasonal Adjustment Methods When Forecasting Intraday Volatilityen_US
dc.type (資料類型) articleen