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.

CRRA utility functions, Most entropic copulas, Rank correlations, Shannon entropy, The Kullback-Leibler cross entropy
Journal of Banking and Finance
Department of Economics

Chu, B. (2011). Recovering copulas from limited information and an application to asset allocation. Journal of Banking and Finance, 35(7), 1824–1842. doi:10.1016/j.jbankfin.2010.12.011