Statistical Properties of the Asymmetric Power ARCH Process

Changli He () and Timo Teräsvirta
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Changli He: Dept. of Economic Statistics, Stockholm School of Economics, Postal: Stockholm School of Economics, P.O. Box 6501, S-113 83 Stockholm, Sweden

No 199, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

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 (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 21 pages
Date: 1997-09-26, Revised 1997-09-30
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Citations: View citations in EconPapers (6)

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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Persistent link: https://EconPapers.repec.org/RePEc:hhs:hastef:0199

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