Department of Economics and Business Economics

Timo Teräsvirta

Modelling volatility by variance decomposition

Research output: ResearchWorking paper

Standard

Modelling volatility by variance decomposition. / Amado, Cristina; Teräsvirta, Timo.

Aarhus : CREATES, Institut for Økonomi, Aarhus Universitet, 2011.

Research output: ResearchWorking paper

Harvard

Amado, C & Teräsvirta, T 2011 'Modelling volatility by variance decomposition' CREATES, Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Amado, C., & Teräsvirta, T. (2011). Modelling volatility by variance decomposition. Aarhus: CREATES, Institut for Økonomi, Aarhus Universitet.

CBE

Amado C, Teräsvirta T. 2011. Modelling volatility by variance decomposition. Aarhus: CREATES, Institut for Økonomi, Aarhus Universitet.

MLA

Amado, Cristina and Timo Teräsvirta Modelling volatility by variance decomposition. Aarhus: CREATES, Institut for Økonomi, Aarhus Universitet. 2011., 43 p.

Vancouver

Amado C, Teräsvirta T. Modelling volatility by variance decomposition. Aarhus: CREATES, Institut for Økonomi, Aarhus Universitet. 2011.

Author

Amado, Cristina ; Teräsvirta, Timo. / Modelling volatility by variance decomposition. Aarhus : CREATES, Institut for Økonomi, Aarhus Universitet, 2011.

Bibtex

@techreport{c1b471dc9101455694cd23574b03aa28,
title = "Modelling volatility by variance decomposition",
abstract = "In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the conditional and unconditional variances where the transition between regimes over time is smooth. The main focus is on the multiplicative decomposition that decomposes the variance into an unconditional and conditional component. A modelling strategy for the time-varying GARCH model based on the multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspecification tests. Finite-sample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice. The results show that the long memory type behaviour of the sample autocorrelation functions of the absolute returns can also be explained by deterministic changes in the unconditional variance.",
keywords = "Conditional heteroskedasticity; Structural change; Lagrange multiplier test;",
author = "Cristina Amado and Timo Teräsvirta",
year = "2011",
publisher = "CREATES, Institut for Økonomi, Aarhus Universitet",
type = "WorkingPaper",
institution = "CREATES, Institut for Økonomi, Aarhus Universitet",

}

RIS

TY - UNPB

T1 - Modelling volatility by variance decomposition

AU - Amado,Cristina

AU - Teräsvirta,Timo

PY - 2011

Y1 - 2011

N2 - In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the conditional and unconditional variances where the transition between regimes over time is smooth. The main focus is on the multiplicative decomposition that decomposes the variance into an unconditional and conditional component. A modelling strategy for the time-varying GARCH model based on the multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspecification tests. Finite-sample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice. The results show that the long memory type behaviour of the sample autocorrelation functions of the absolute returns can also be explained by deterministic changes in the unconditional variance.

AB - In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the conditional and unconditional variances where the transition between regimes over time is smooth. The main focus is on the multiplicative decomposition that decomposes the variance into an unconditional and conditional component. A modelling strategy for the time-varying GARCH model based on the multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspecification tests. Finite-sample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice. The results show that the long memory type behaviour of the sample autocorrelation functions of the absolute returns can also be explained by deterministic changes in the unconditional variance.

KW - Conditional heteroskedasticity; Structural change; Lagrange multiplier test;

M3 - Working paper

BT - Modelling volatility by variance decomposition

PB - CREATES, Institut for Økonomi, Aarhus Universitet

ER -