HEAVY-TAILED DISTRIBUTIONS AND THE CANADIAN STOCK MARKET RETURNS
Journal Title: Copernican Journal of Finance & Accounting - Year 2017, Vol 6, Issue 2
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.
Authors and Affiliations
David Eden, Paul Huffman, John Holman
Keywords
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- EP ID EP246386
- DOI 10.12775/CJFA.2017.007
- Views 68
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