Simultaneously Modelling Conditional Heteroskedasticity and Scale Change

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FENG, Yuanhua, 2002. Simultaneously Modelling Conditional Heteroskedasticity and Scale Change

@techreport{Feng2002Simul-12068, series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie}, title={Simultaneously Modelling Conditional Heteroskedasticity and Scale Change}, year={2002}, number={2002/12}, author={Feng, Yuanhua} }

application/pdf 2002 deposit-license 2011-03-25T09:42:28Z Feng, Yuanhua eng 2011-03-25T09:42:28Z Simultaneously Modelling Conditional Heteroskedasticity and Scale Change This paper proposes a semiparametric approach by introducing a smooth scale function into the standard GARCH model so that conditional heteroskedasticity and scale change in a financial time series can be modelled simultaneously. An estimation procedure combining kernel estimation of the scale function and maximum likelihood estimation of the GARCH parameters is proposed. Asymptotic properties of the kernel estimator are investigated in detail. An iterative plug-in algorithm is developed for selecting the bandwidth. Practical performance of the proposal is illustrated by simulation. The proposal is applied to the daily S&P 500 and DAX 100 returns. It is shown that there are simultaneously significant conditional heteroskedasticity and scale change in these series. Feng, Yuanhua

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02-12.pdf 39

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