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• W2264942019 abstract "The volatility prediction is the most important issue in finance, as it is the key ingredient variable in forecasting the prices of options, the VaR number and, in general, the risk that investors face. By estimating not only inter-day volatility models that capture the main characteristics of asset returns, such as the non-zero skewness, the excess kurtosis relative to that of the normal distribution and the fractional integration of the conditional variance, but also an intra-day model, we investigate their forecasting performance for three European equity indices. We find out that there is no consistent relation between the examined models and the specific purpose of volatility forecasts. Researchers cannot apply, not even for the same equity index, one model for all the forecasting purposes. However, if they want to choose one model, they must prefer an inter-day specification that accounts at least for volatility clustering and the leverage effect." @default.
• W2264942019 created "2016-06-24" @default.
• W2264942019 creator A5003074891 @default.
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• W2264942019 date "2005-01-01" @default.
• W2264942019 modified "2023-09-26" @default.
• W2264942019 title "Volatility Forecasting: The Illusion of Choosing One Model in All Cases" @default.
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• W2264942019 doi "https://doi.org/10.2139/ssrn.808029" @default.
• W2264942019 hasPublicationYear "2005" @default.
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