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Heavy-Tailed Distributions And The Canadian Stock Market Returns

Author

Listed:
  • David Eden
  • Paul Huffman
  • John Holman

    (Bank of Canada
    University of Manitoba
    Illinois State University)

Abstract

Many of financial engineering theories are based on so-called “complete markets” and on the use of the Black-Scholes formula. The formula relies on the assumption that asset prices follow a log-normal distribution, or in other words, the daily fluctuations in prices viewed as percentage changes follow a Gaussian distribution. On the contrary, studies of actual asset prices show that they do not follow a log-normal distribution. In this paper, we investigate several widely-used heavy-tailed distributions. Our results indicate that the Skewed t distribution has the best empirical performance in fitting the Canadian stock market returns. We claim the results are valuable for market participants and the financial industry.

Suggested Citation

  • David Eden & Paul Huffman & John Holman, 2017. "Heavy-Tailed Distributions And The Canadian Stock Market Returns," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 6(2), pages 9-21.
  • Handle: RePEc:cpn:umkcjf:v:6:y:2017:i:2:p:9-21
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