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EnglishMany 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.
| Titolo: | Evaluation of volatility forecasts in a VaR framework |
| Autori: | |
| Data di pubblicazione: | 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. |
| Handle: | http://hdl.handle.net/11386/4424855 |
| ISBN: | 9783319050133 |
| Appare nelle tipologie: | 2.1.2 Articolo su libro con ISBN |
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