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• W3024003503 abstract "Nowadays, a common method to forecast integrated variance is to use the fitted value of a simple OLS autoregression of the realized variance. However, non-parametric estimates of the tail index of this realized variance process reveal that its second moment is possibly unbounded. In this case, the behavior of the OLS estimators and the corresponding statistics are unclear. We prove that when the second moment of the spot variance is unbounded, the slope of the spot variance’s autoregression converges to a random variable as the sample size diverges. The same result holds when one uses the integrated or realized variance instead of the spot variance. We then consider the class of diffusion variance models with an affine drift, a class which includes GARCH and CEV processes, and we prove that IV estimation with adequate instruments provide consistent estimators of the drift parameters as long as the variance process has a finite first moment regardless of the existence of the second moment. In particular, for the GARCH diffusion model with fat tails, an IV estimation where the instrument equals the sign of the centered lagged value of the variable of interest provides consistent estimators. Simulation results corroborate the theoretical findings of the paper." @default.
• W3024003503 created "2020-05-21" @default.
• W3024003503 creator A5059545223 @default.
• W3024003503 creator A5091510154 @default.
• W3024003503 date "2020-10-01" @default.
• W3024003503 modified "2023-09-23" @default.
• W3024003503 title "Volatility regressions with fat tails" @default.
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• W3024003503 doi "https://doi.org/10.1016/j.jeconom.2020.04.034" @default.
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