Modeling Returns Distribution Based upon Radical Normal Distributions

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概要

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• The main subject of this paper is to develop a heuristic method to identify returns distribution of an asset or a portfolio more accurately than the well-assumed conventional distributions do, such as, normal, lognormal, or stable distribution. Certainly any distributional assumption has its own merits. But, these conventional assumptions are inconsistent with the empirical analysis since either a distributional assumption cannot catch excess kurtosis and fat tails, or has no finite moments so far. Thus, it could cause a great deal of bias when applied to risk management, i.e., evaluation of the Value at Risk. Here we propose heuristic method to identify returns distribution by using a mixture distribution constructed by a linear combination (or weighed sum) of some distributions. And the distributional parameters and weight coefficients are to be optimized by the Genetic Algorithm.

• 久留米大学の論文
• 2005-12-25

著者

• Tan Kangrong

  Faculty Of Economics Kurume University

• Tan Kangrong

  Faculty of Economics, Kurume University

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