Modelling and forecasting WIG20 daily returns

Cristina Amado (), Annastiina Silvennoinen and Timo Teräsvirta
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Annastiina Silvennoinen: School of Economics and Finance, Queensland University of Technology

No 09/2017, NIPE Working Papers from NIPE - Universidade do Minho

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
New Economics Papers: this item is included in nep-ecm and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Related works:
Journal Article: Modelling and Forecasting WIG20 Daily Returns (2017)
Working Paper: Modelling and forecasting WIG20 daily returns (2017)
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