Estimating and forecasting instantaneous volatility through a duration model : An assessment based on VaR
AbstractIn order to forecast one-step ahead volatility, we calculated jump intensity by using estimated parameters of a duration model of price change. In this procedure, we do not assume any distribution on log-return. Although we do not make any distributional assumption, we may practically choose a suitable distribution e.g. Normal, student, etc, including empirical density, when we calculate a VaR (Value at Risk) with an instantaneous volatility to check the prediction performance. Furthermore, we compare the goodness of fit among assumed distributions of log-return. We find that fat tail distributions such as NIG, Laplace, are well fitted to the actual high frequency data listed on the Tokyo stock exchange 1st section from 4 Jan. 2001 to 28 June 2001
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Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society 2004 Far Eastern Meetings with number 592.
Date of creation: 11 Aug 2004
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High frequency data; Duration model; Instantaneous volatility; VaR;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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