Statistical Properties of the Asymmetric Power ARCH Process
AbstractThe 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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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 199.
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.
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GARCH; heteroskedasticity; financial time series; nonlinearity; S&P 500; volatility; time series;
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