Sharpe style analysis in the msci sector portfolios: a monte carlo integration approach

Abstract

We examine a decision-theoretic Bayesian framework for the estimation of Sharpe Style portfolio weights of the MSCI sector returns. Following [van Dijk and Kloek (1980)] an appropriately defined prior density of style weights can incorporate non-negativity and other constraints. We use factor-mimicking portfolios as proxies to global style factors such as Value, Growth, Debt and Size. Our computational approach is based on Monte Carlo Integration (MCI) of [Kloek and van Dijk (1978)] for the estimation of the posterior moments and distribution of portfolio weights. MCI provides a number of advantages, such as a flexible choice of prior distributions, improved numerical accuracy of the estimated parameters, the use of inequality restrictions in prior distributions and exact inference procedures. Our empirical findings suggest that, contrary to existing evidence, style factors do explain the MSCI sector portfolio returns for the particular sample period. Further, non-negativity constraints on portfolio weights were found to be binding in all cases.