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Testing constancy of unconditional variance in volatility models by misspecification and specification tests

Testing constancy of unconditional variance in volatility models by misspecification and... AbstractThe topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH model to the original series. It is found by simulation that the positive size distortion present in these tests is a function of the kurtosis of the GARCH process. Adjusting the size by numerical methods is considered. The possibility of testing the constancy of the unconditional variance before fitting a GARCH model to the data is discussed. The power of the ensuing test is vastly superior to that of the misspecification test and the size distortion minimal. The test has reasonable power already in very short time series. It would thus serve as a test of constant variance in conditional mean models. An application to exchange rate returns is included. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Nonlinear Dynamics & Econometrics de Gruyter

Testing constancy of unconditional variance in volatility models by misspecification and specification tests

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Publisher
de Gruyter
Copyright
©2016 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1558-3708
eISSN
1558-3708
DOI
10.1515/snde-2015-0033
Publisher site
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Abstract

AbstractThe topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH model to the original series. It is found by simulation that the positive size distortion present in these tests is a function of the kurtosis of the GARCH process. Adjusting the size by numerical methods is considered. The possibility of testing the constancy of the unconditional variance before fitting a GARCH model to the data is discussed. The power of the ensuing test is vastly superior to that of the misspecification test and the size distortion minimal. The test has reasonable power already in very short time series. It would thus serve as a test of constant variance in conditional mean models. An application to exchange rate returns is included.

Journal

Studies in Nonlinear Dynamics & Econometrics – de Gruyter

Published: Sep 1, 2016

References

  • Specification and Testing of Multiplicative Time-varying GARCH Models with Applications
  • Modelling Volatility by Variance Decomposition
  • Inequality Constraints in the Univariate GARCH Model
  • Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-varying Structure
  • Modelling Changes in the Unconditional Variance of Long Stock Return Series
  • North American Oriented Strand Board Markets, Arbitrage Activity, and Market Price Dynamics: A Smooth Transition Approach
  • An Introduction to Univariate GARCH Models
  • Comparison of Volatility Measures: A Risk Management Perspective
  • Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach
  • Simultaneously Modeling Conditional Heteroskedasticity and Scale Change
  • Neglecting Parameter Changes in GARCH Models