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.
Evaluation of volatility forecasts in a VaR framework / Amendola, Alessandra; Candila, Vincenzo. - (2014), pp. 7-11.
Evaluation of volatility forecasts in a VaR framework
Alessandra Amendola;Vincenzo Candila
2014
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.File | Dimensione | Formato | |
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