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The Economic Research Institute, Stockholm School of Economics SSE/EFI Working Paper Series in Economics and Finance

No 199:
Statistical Properties of the Asymmetric Power ARCH Process

Changli He () and Timo Teräsvirta ()

Abstract: 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.

Keywords: GARCH; heteroskedasticity; financial time series; nonlinearity; S&P 500; volatility; time series; (follow links to similar papers)

JEL-Codes: C22; (follow links to similar papers)

21 pages, September 26, 1997, Revised September 30, 1997

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This paper is published as:
He, Changli and Timo Teräsvirta, (1999), 'Statistical Properties of the Asymmetric Power ARCH Process' in Engle, Robert F. and Halbert White (eds.) Cointegration, causality, and forecasting. Festschrift in honour of Clive W.J. Granger, chapter 19, pages 462-474, Oxford University Press.



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