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Abnormal returns, risk, and options in large data sets

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  • S. Caserta
  • J. DanÃÂÃÂelsson
  • C. G. De Vries

Abstract

Large data sets in finance with millions of observations have become widely available. Such data sets enable the construction of reliable semi‐parametric estimates of the risk associated with extreme price movements. Our approach is based on semi‐parametric statistical extreme value analysis, and compares favorably with the conventional finance normal distribution based approach. It is shown that the efficiency of the estimator of the extreme returns may benefit from high frequency data. Empirical tail shapes are calculated for the German Mark—US Dollar foreign exchange rate, and we use the semi‐parametric tail estimates in combination with the empirical distribution function to evaluate the returns on exotic options.

Suggested Citation

  • S. Caserta & J. DanÃÂÃÂelsson & C. G. De Vries, 1998. "Abnormal returns, risk, and options in large data sets," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 52(3), pages 324-335, November.
    • Handle: RePEc:bla:stanee:v:52:y:1998:i:3:p:324-335
    DOI: 10.1111/1467-9574.00087
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    References listed on IDEAS

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    1. Boyle, Phelim P., 1977. "Options: A Monte Carlo approach," Journal of Financial Economics, Elsevier, vol. 4(3), pages 323-338, May.
    2. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    3. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Byström, Hans, 2003. "Estimating Default Probabilities Using Stock Prices: The Swedish Banking Sector During the 1990s Banking Crisis," Working Papers 2003:1, Lund University, Department of Economics.
    2. Danielsson, Jon, 2002. "The emperor has no clothes: Limits to risk modelling," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1273-1296, July.

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