Evaluation of Volatility Forecasts in a VaR Framework

Alessandra Amendola () and Vincenzo Candila ()
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Vincenzo Candila: University of Salerno, Dept. of Economics and Statistics

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2014, pp 7-10 from Springer

Abstract: Abstract Many methods can be considered to select which volatility model has a better forecast accuracy. In this work a loss function approach in a Value at Risk (VaR) framework is chosen. By using high-frequency data it is possible to achieve a consistent estimate of the VaR bootstrapping the intraday increments of an asset. The VaR estimate is used to find a threshold discriminating low from high loss function values. The analysis concerns the high-frequency data of a stock listed on the New York Stock Exchange.

Keywords: Volatility; Value at Risk; Loss function; Bootstrap (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-05014-0_2

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DOI: 10.1007/978-3-319-05014-0_2

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