He, Changli () (Dept. of Economic Statistics, Stockholm School of Economics) Teräsvirta, Timo () (Dept. of Economic Statistics, Stockholm School of Economics)
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The asymmetric power ARCH model is a recent addition to time series models that may be used for predicting volatility. Its performance is compared with that of standard models of conditional heteroskedasticity such as GARCH. This has previously been done empirically. In this paper the same issue is studied theoretically using unconditional fractional moments for the A-PARCH model that are derived for the purpose. The role of the heteroskedasticity parameter of the A-PARCH process is highlighted and compared with corresponding empirical results involving autocorrelation functions of power-transformed absolute-valued return series.
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Length: 21 pages Date of creation: 26 Sep 1997 Date of revision:
30 Sep 1997 Publication status: Published in Cointegration, causality, and forecasting. Festschrift in honour of Clive W.J. Granger, Engle, Robert F., White, Halbert (eds.), 1999, chapter 19, pages 462-474, Oxford University Press. Handle: RePEc:hhs:hastef:0199
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Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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