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Moment condition failure in high frequency financial data: evidence from the S&P 500

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  • A. Abhyankar
  • L. S. Copeland
  • W. Wong

Abstract

Loretan-Phillips maximal moment exponent estimators are used to investigate the distribution of S&P 500 stock returns at a range of different frequencies. In all cases, the variance is found to be finite, but the existence of higher-order moments is in some doubt.

Suggested Citation

  • A. Abhyankar & L. S. Copeland & W. Wong, 1995. "Moment condition failure in high frequency financial data: evidence from the S&P 500," Applied Economics Letters, Taylor & Francis Journals, vol. 2(8), pages 288-290.
    • Handle: RePEc:taf:apeclt:v:2:y:1995:i:8:p:288-290
    DOI: 10.1080/135048595357258
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    References listed on IDEAS

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    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. Jansen, Dennis W & de Vries, Casper G, 1991. "On the Frequency of Large Stock Returns: Putting Booms and Busts into Perspective," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 18-24, February.
    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.
    4. Peter C.B. Phillips & Mico Loretan, 1990. "Testing Covariance Stationarity Under Moment Condition Failure with an Application to Common Stock Returns," Cowles Foundation Discussion Papers 947, Cowles Foundation for Research in Economics, Yale University.
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    Cited by:

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    4. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
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