Forecasting irregularly spaced UHF financial data: Realized volatility vs UHF-GARCH models

被引：13
作者：
Racicot F.-E. [1 ,2 ,3 ]
Théoret R. [3 ]
Coën A. [3 ]
机构：
[1] Department of Administrative Sciences, University of Quebec-Outaouais (UQO), Gatineau, QC J8Y 3J5
[2] Laboratory for Research in Statistics and Probability (LRSP), Carleton University, University of Ottawa, Ottawa, ON
[3] re et Organisationnelle, ESG-UQAM, Montreal, QC
[4] Department of Business Strategy, University of Quebec-Montréal (UQAM), Montreal, QC H2X-3X2, 315 est, Ste-Catherine
来源：
International Advances in Economic Research | 2008年 / 14卷 / 1期
关键词：
Daily VaR; Financial markets; Historical simulation; Realized volatility; Time deformation; UHF-GARCH;
D O I：
10.1007/s11294-008-9134-2
中图分类号：
学科分类号：
摘要：
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). © International Atlantic Economic Society 2008.
引用
收藏
页码：112 / 124
页数：12
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