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- W2012808839 abstract "There is considerable evidence that GARCH models do not forecast financial volatility well out of sample when evaluated by the R 2 from the Mincer and Zarnowitz (1969) regression. Andersen and Bollerslev (1998) argued that although the R 2s tend to be small, they are consistent with the population value of the criterion for a correctly specified GARCH model. We extend the Andersen and Bollerslev result and derive the population moments of the mean squared error, the mean absolute error and a heteroscedasticity adjusted mean square error for the GARCH volatility forecasts. We state existence conditions for the moments. The criteria and their population values are illustrated with empirical examples. Using Monte Carlo simulation, we analyse the sampling properties of these criteria. When volatility is highly persistent, we find that the sampling distribution of the R 2 is highly skewed to the right, which indicates that the majority of the realized R 2s lie below the population R 2. Among the accuracy crite..." @default.
- W2012808839 created "2016-06-24" @default.
- W2012808839 creator A5087099710 @default.
- W2012808839 date "2007-05-01" @default.
- W2012808839 modified "2023-09-26" @default.
- W2012808839 title "Sampling properties of criteria for evaluating GARCH volatility forecasts" @default.
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- W2012808839 doi "https://doi.org/10.1080/09603100600735294" @default.
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