Department of Economics and Business Economics

Modelling and forecasting WIG20 daily returns

Research output: Working paperResearch

Standard

Modelling and forecasting WIG20 daily returns. / Amado, Cristina; Silvennoinen, Annestiina; Terasvirta, Timo.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2017.

Research output: Working paperResearch

Harvard

Amado, C, Silvennoinen, A & Terasvirta, T 2017 'Modelling and forecasting WIG20 daily returns' Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Amado, C., Silvennoinen, A., & Terasvirta, T. (2017). Modelling and forecasting WIG20 daily returns. Aarhus: Institut for Økonomi, Aarhus Universitet. CREATES Research Papers, No. 2017-29

CBE

Amado C, Silvennoinen A, Terasvirta T. 2017. Modelling and forecasting WIG20 daily returns. Aarhus: Institut for Økonomi, Aarhus Universitet.

MLA

Amado, Cristina, Annestiina Silvennoinen, and Timo Terasvirta Modelling and forecasting WIG20 daily returns. Aarhus: Institut for Økonomi, Aarhus Universitet. (CREATES Research Papers; Journal number 2017-29). 2017., 31 p.

Vancouver

Amado C, Silvennoinen A, Terasvirta T. Modelling and forecasting WIG20 daily returns. Aarhus: Institut for Økonomi, Aarhus Universitet. 2017 Sep 4.

Author

Amado, Cristina ; Silvennoinen, Annestiina ; Terasvirta, Timo. / Modelling and forecasting WIG20 daily returns. Aarhus : Institut for Økonomi, Aarhus Universitet, 2017. (CREATES Research Papers; No. 2017-29).

Bibtex

@techreport{cff7b9d1dd8c454f95d35165b237eef3,
title = "Modelling and forecasting WIG20 daily returns",
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",
author = "Cristina Amado and Annestiina Silvennoinen and Timo Terasvirta",
year = "2017",
month = "9",
day = "4",
language = "English",
publisher = "Institut for {\O}konomi, Aarhus Universitet",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, Aarhus Universitet",

}

RIS

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T1 - Modelling and forecasting WIG20 daily returns

AU - Amado,Cristina

AU - Silvennoinen,Annestiina

AU - Terasvirta,Timo

PY - 2017/9/4

Y1 - 2017/9/4

N2 - 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.

AB - 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.

KW - Autoregressive conditional heteroskedasticity, forecasting volatility, modelling volatility, multiplicative time-varying GARCH, smooth transition

M3 - Working paper

BT - Modelling and forecasting WIG20 daily returns

PB - Institut for Økonomi, Aarhus Universitet

CY - Aarhus

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