Description

• Title:
  HEAVY-TAILED DISTRIBUTIONS AND THE CANADIAN STOCK MARKET RETURNS
• Creator:
  Eden, David;
  Huffman, Paul;
  Holman, John
• Description:
  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.
• Object availability:
  free access
• Rights:
  Prawa autorskie (c) 2017 Copernican Journal of Finance & Accounting
• Date:
  2017.12.08
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Language:
  English
• Source:
  Copernican Journal of Finance & Accounting; Vol. 6 No. 2 (2017); 9-21;
  Copernican Journal of Finance & Accounting; Tom 6 Nr 2 (2017); 9-21;
  2300-3065;
  2300-1240
• Format:
  application/pdf
• Publisher:
  Uniwersytet Mikołaja Kopernika w Toruniu
• Relation: https://apcz.umk.pl/CJFA/article/view/CJFA.2017.007/13533
• Subject:
  Value at Risk;
  GSPTSE;
  Skewed t distribution;
  C46;
  C58;
  G10
• Identifier: https://apcz.umk.pl/CJFA/article/view/CJFA.2017.007
• Data provider:
  Akademicka Platforma Czasopism
• Can I use it?:
  seek permission
• Type:
  text