Atomic portfolio selection: MVSK utility optimization of global real estate securities

Abstract

With the recent nascent of the first real estate hedge fund in Asia in July 2004 in the burgeoning hedge fund industry, more research is due for global real estate securities. This thesis addresses global real estate securities by analyzing risks-returns and portfolio selection strategies in a four-moment mean-variance-skewness-kurtosis (MVSK) framework. By modeling higher moment CAPMs with GMM estimation, which account for the co-moments of covariance, coskewness and cokurtosis, we empirically identify three co-moment conditions of anti-moment, bi-moments and tri-moments in individual securities of a portfolio. We show Atomic Portfolio Selection (APS) as the process that incorporates the three co-moments of individual securities and the key identification of the three atomic co-moment conditions of each security. Additionally, we perform a time-varying Kalman Filter analysis of conditional co-moments and find that significant higher moments are time-varying. Our results support higher moment modeling in real estate securities and the MVSK models reveal to be a more conservative approach for portfolio construction.