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The power of some standard tests of stationarity against changes in the unconditional variance

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  • Ibrahim Ahamada

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Mohamed Boutahar

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Abrupt changes in the unconditional variance of returns have been recently revealed in many empirical studies. In this paper, we show that traditional KPSS-based tests have a low power against nonstationarities stemming from changes in the unconditional variance. More precisely, we show that even under very strong abrupt changes in the unconditional variance, the asymptotic moments of the statistics of these tests remain unchanged. To overcome this problem, we use some CUSUM-based tests adapted for small samples. These tests do not compete with KPSS-based tests and can be considered as complementary. CUSUM-based tests confirm the presence of strong abrupt changes in the unconditional variance of stock returns, whereas KPSS-based tests do not. Consequently, traditional stationary models are not always appropriate to describe stock returns. Finally, we show how a model allowing abrupt changes in the unconditional variance is well appropriate for CAC 40 stock returns.

Suggested Citation

  • Ibrahim Ahamada & Mohamed Boutahar, 2010. "The power of some standard tests of stationarity against changes in the unconditional variance," Post-Print halshs-00476024, HAL.
    • Handle: RePEc:hal:journl:halshs-00476024
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00476024
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    References listed on IDEAS

    as
    1. Ibrahim Ahamada & Jamel Jouini & Mohamed Boutahar, 2004. "Detecting multiple breaks in time series covariance structure: a non-parametric approach based on the evolutionary spectral density," Applied Economics, Taylor & Francis Journals, vol. 36(10), pages 1095-1101.
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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