文章基本信息

标题：HEAVY-TAILED DISTRIBUTIONS AND THE CANADIAN STOCK MARKET RETURNS
本地全文：下载
作者：DAVID EDEN ; DAVID EDEN ; PAUL HUFFMAN 等
期刊名称：Copernican Journal of Finance & Accounting
印刷版ISSN：2300-1240
电子版ISSN：2300-3065
出版年度：2017
卷号：6
期号：2
页码：9-21
DOI：10.12775/CJFA.2017.007
语种：English
出版社：Nicolaus Copernicus University Press
摘要：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.
关键词：alue at Risk; GSPTSE; Skewed t distribution