Forecasting Volatility Using A Continuous Time Model
AbstractThis paper evaluates the forecasting performance of a continuous stochastic volatility model with two factors of volatility (SV2F) and compares it to those of GARCH and ARFIMA models. The empirical results show that the volatility forecasting ability of the SV2F model is better than that of the GARCH and ARFIMA models, especially when volatility seems to change pattern. We use ex-post volatility as a proxy of the realized volatility obtained from intraday data and the forecasts from the SV2F are calculated using the reprojection technique proposed by Gallant and Tauchen (1998).
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Bibliographic InfoPaper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number 584.03.
Date of creation: 04 Sep 2003
Date of revision:
Efficient Method of Moments (EMM); Reprojection; Factors of Volatility; Fractional Integration; Volatility Forecasting.;
Find related papers by JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
This paper has been announced in the following NEP Reports:
- NEP-CFN-2003-09-14 (Corporate Finance)
- NEP-ECM-2003-09-14 (Econometrics)
- NEP-ETS-2003-09-14 (Econometric Time Series)
- NEP-FMK-2003-09-14 (Financial Markets)
- NEP-RMG-2003-09-14 (Risk Management)
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