This dissertation contains five chapters. An introduction and a summary of the research are given in Chapter 1. The other four chapters present theoretical results on the moment structure of GARCH processes. Some chapters also contain empirical examples in order to illustrate applications of the theory. The focus, however, is mainly on statistical theory. Chapter 2 considers the moments of a family of first-order GARCH processes. First, a general condition of the existence of any integer moment of the absolute values of the observations is given. Second, a general expression of this moments as a function of lower-order moments is derived. Third, the kurtosis and the autocorrelation function of the squared and absolute-valued observations are derived. The results apply to a host of different GARCH parameterizations. Finally, the existence, or the lack of it, of the theoretical counterpart to the so-called Taylor effect for some members of this GARCH family is discussed. 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 Chapter 3 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.In Chapter 4, a necessary and sufficient condition for the existence of the unconditional fourth moment of the GARCH(p,q) process is given as well as an expression for the moment itself. Furthermore, the autocorrelation function of the centred and squared observations of this process is derived. The statistical theory is further illustrated by a few special cases such as the GARCH(2,2) process and the ARCH(q) process.Nonnegativity constraints on the parameters of the GARCH(p,q) model may be relaxed without giving up the requirement of the conditional variance remaining nonnegative with probability one. Chapter 5 looks into the consequences of adopting these less severe constraints in the GARCH(2,2) case and its two second-order special cases, GARCH(2,1) and GARCH(1,2). This is done by comparing the autocorrelation function of squared observations under these two sets of constraints. The less severe constraints allow more flexibility in the shape of the autocorrelation function than the constraints restricting the parameters to be nonnegative. The theory is illustrated by an empirical example. / Revised versions of chapters 2-5 have been published as:He, C. and T. Teräsvirta, "Properties of moments of a amily of GARCH processes" in Journal of Econometrics, Vol. 92, No. 1, 1999, pp173-192.He, C. and T. Teräsvirta, "Statistical Properties of the Asymmetric Power ARCH Process" in R.F. Engle and H. White (eds) Cointegration, causality, and forecasting. Festschrift in honour of Clive W.J. Granger, chapter 19, pp 462-474, Oxford University Press, 1999.He, C. and T. Teräsvirta, "Fourth moment structure of the GARCH(p,q) process" in Econometric Theory, Vol. 15, 1999, pp 824-846.He, C. and T. Teräsvirta, "Properties of the autocorrelation function of squared observations for second order GARCH processes under two sets of parameter constraints" in Journal of Time Series Analysis, Vol. 20, No. 1, January 1999, pp 23-30.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hhs-850 |
Date | January 1997 |
Creators | He, Changli |
Publisher | Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), Stockholm : Economic Research Insitute, Stockholm School of Economics [Ekonomiska forskningsinstitutet vid Handelshögsk.] (EFI) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, monograph, info:eu-repo/semantics/doctoralThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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