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Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models |
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| Authors: | François-Éric Racicot Raymond Théoret Alain Coën |
| Affiliation: | 1.Department of Administrative Sciences,University of Quebec–Outaouais (UQO),Gatineau,Canada;2.Laboratory for Research in Statistics and Probability (LRSP) affiliated with Carleton University, University of Ottawa, and UQO,Ottawa,Canada;3.Chaire d’information financière et organisationnelle,ESG-UQAM,Montreal,Canada;4.Department of Business Strategy,University of Quebec–Montréal (UQAM),Montreal,Canada |
| Abstract: | A new literature has been recently devoted to the modeling of ultra-high-frequency (UHF) data. Our first aim is to develop an empirical application of UHF-GARCH models to forecast future volatilities on irregularly spaced data. We also compare the out-sample performance of these generalized autoregressive conditional heteroskedastic (GARCH) models with the realized volatility method. We propose a procedure to account for the time deformation problem and show how to use these models for computing daily Value at Risk (VaR). |
| Keywords: | Realized volatility UHF-GARCH Time deformation Financial markets Daily VaR Historical simulation |
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