Modelling Volatility by Variance Decomposition

Cristina Amado () and Timo Teräsvirta

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

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 misspeci?cation 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; Misspeci?cation test; Nonlinear time series; Time-varying parameter model. (search for similar items in EconPapers)
JEL-codes: C12 C22 C51 C52 (search for similar items in EconPapers)
Pages: 45
Date: 2011-01-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Related works:
Journal Article: Modelling volatility by variance decomposition (2013)
Working Paper: Modelling Volatility by Variance Decomposition (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2011-01

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