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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. 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.
    2. 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.
    3. 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.
    4. 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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    Cited by:

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