Recovering copulas from limited information and an application to asset allocation
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.
|Keywords||CRRA utility functions, Most entropic copulas, Rank correlations, Shannon entropy, The Kullback-Leibler cross entropy|
|Journal||Journal of Banking and Finance|
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