Recovering copulas from limited information and an application to asset allocation

被引：26

作者：

Chu, Ba ^{[1
]}

机构：

[1] Carleton Univ, Dept Econ, Ottawa, ON K1S 5B6, Canada

来源：

JOURNAL OF BANKING & FINANCE | 2011年 / 35卷 / 07期

关键词：

Shannon entropy; Most entropic copulas; The Kullback-Leibler cross entropy; Rank correlations; CRRA utility functions; EXPECTED STOCK RETURNS; RANK CORRELATION; ENTROPY ECONOMETRICS; DISTRIBUTIONS; DEPENDENCE; RISK; MARKETS; DENSITY; TESTS;

D O I：

10.1016/j.jbankfin.2010.12.011

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

This paper proposes an entropy-based method to construct a new class of copulas - the most entropic canonical copulas (MECC). Our empirical study focuses on an investment problem for an investor with a constant relative risk aversion (CRRA) utility function allocating wealth between the Dow Jones Large-Cap and Small-Cap indices, of which the contemporaneous dependence can be modeled by the MECC or other commonly-used copulas. Both the theoretical analysis of the method and the empirical study indicate the potential for enormous statistical and economic gains as a result of using the MECC. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：1824 / 1842

页数：19

共 41 条

[11] THE BEHAVIOR OF STOCK-MARKET PRICES [J].