Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models
AbstractA very promising literature has been recently devoted to the modeling of ultra-high-frequency (UHF) data. Our first aim is to develop an empirical application of Autoregressive Conditional Duration GARCH models and the realized volatility to forecast future volatilities on irregularly spaced data. We also compare the out sample performances of ACD GARCH models with the realized volatility method. We propose a procedure to take into account the time deformation and show how to use these models for computing daily VaR.
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Length: 27 pages
Date of creation: 06 Jul 2006
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Realized volatility; Ultra High Frequency GARCH; time deformation; financial markets; Daily VaR.;
Other versions of this item:
- François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer, vol. 14(1), pages 112-124, February.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-07-15 (All new papers)
- NEP-BEC-2006-07-15 (Business Economics)
- NEP-ECM-2006-07-15 (Econometrics)
- NEP-ETS-2006-07-15 (Econometric Time Series)
- NEP-FIN-2006-07-15 (Finance)
- NEP-FMK-2006-07-15 (Financial Markets)
- NEP-FOR-2006-07-15 (Forecasting)
- NEP-MST-2006-07-15 (Market Microstructure)
- NEP-RMG-2006-07-15 (Risk Management)
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