Estimating and forecasting instantaneous volatility through a duration model: An assessment based on VaR

Takayki Morimoto

No 592, Econometric Society 2004 Far Eastern Meetings from Econometric Society

Abstract: In 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

Keywords: High frequency data; Duration model; Instantaneous volatility; VaR (search for similar items in EconPapers)
JEL-codes: C13 C14 C15 (search for similar items in EconPapers)
Date: 2004-08-11
New Economics Papers: this item is included in nep-fin
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Persistent link: https://EconPapers.repec.org/RePEc:ecm:feam04:592

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