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Non stationarity characteristics of the S\&P500 returns:An approach based on the evolutionary spectral density

Author

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  • AHAMADA IBRAHIM

    (GREQAM, université de la méditerranée and CERESUR, université de La Réunion)

Abstract

In this paper we study the characteristics of the non stationarity of the covariance structure of the S\&P 500 returns by analyzing the time spectral density of the data. We show that the S\&P 500 returns has the same characteristics as the modulate white noise process. So, some precautions must be taken before applying traditional stationary models to describe like long size financial time series.

Suggested Citation

  • Ahamada Ibrahim, 2003. "Non stationarity characteristics of the S\&P500 returns:An approach based on the evolutionary spectral density," Economics Bulletin, AccessEcon, vol. 3(32), pages 1-7.
    • Handle: RePEc:ebl:ecbull:eb-03c50007
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    References listed on IDEAS

    as
    1. Loretan, Mico & Phillips, Peter C. B., 1994. "Testing the covariance stationarity of heavy-tailed time series: An overview of the theory with applications to several financial datasets," Journal of Empirical Finance, Elsevier, vol. 1(2), pages 211-248, January.
    2. Ahamada, Ibrahim, 2002. "Tests for covariance stationarity and white noise, with an application to Euro/US dollar exchange rate: An approach based on the evolutionary spectral density," Economics Letters, Elsevier, vol. 77(2), pages 177-186, October.
    3. Pagan, Adrian R. & Schwert, G. William, 1990. "Testing for covariance stationarity in stock market data," Economics Letters, Elsevier, vol. 33(2), pages 165-170, June.
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    More about this item

    Keywords

    Time-dependent spectral density unconditional volatility S&P 500 returns.;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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