We propose a new approach to recover relative entropy measures of dependence from limited infor mation by constructing the most entropic copulas (MECs) and their canonical form, namely, the most entropic canonical copula (MECC). In the empirical study, we focus on an application of the MECC theory to a 'style investing' problem for an investor with a constant relative risk aversion (CRRA) utility function allocating wealth between the Russell 1000 'growth' and 'value' indices. We found that, using the data in hand, the gains from using the MECC (vis-à-vis commonly used parametric copulas) to model the dependence between the indices' returns for our investment strategies are economically and statistically significant for the case with/without short-sales constraints.

Additional Metadata
Keywords Asset allocation strategies, CRRA, Financial applications, MECC theory, Monte Carlo simulations, Pearson's correlation coefficient, Relative entropy, Style investment
ISBN 978-1-119-28899-2
Persistent URL dx.doi.org/10.1002/9781119288992.ch10
Citation
Chu, B, & Satchell, S. (Stephen). (2017). The Most Entropie Canonical Copula with an Application to 'Style' Investment. In Assymetric Dependence in Finance: Diversification, Correlation and Portfolio Management in Market Downturns (pp. 221–252). doi:10.1002/9781119288992.ch10