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Modelling and forecasting WIG20 daily returns

Cristina Amado (), Annastiina Silvennoinen and Timo Teräsvirta ()

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: The purpose of this paper is to model daily returns of the WIG20 index. The idea is to consider a model that explicitly takes changes in the amplitude of the clusters of volatility into account. This variation is modelled by a positive-valued deterministic component. A novelty in specification of the model is that the deterministic component is specified before estimating the multiplicative conditional variance component. The resulting model is subjected to misspecification tests and its forecasting performance is compared with that of commonly applied models of conditional heteroskedasticity.

Keywords: Autoregressive conditional heteroskedasticity; forecasting volatility; modelling volatility; multiplicative time-varying GARCH; smooth transition (search for similar items in EconPapers)
JEL-codes: C32 C52 C58 (search for similar items in EconPapers)
Date: 2017-08-31
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ftp://ftp.econ.au.dk/creates/rp/17/rp17_29.pdf (application/pdf)

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Journal Article: Modelling and Forecasting WIG20 Daily Returns (2017) Downloads
Working Paper: Modelling and forecasting WIG20 daily returns (2017) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2017-29

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