Author(s)

Rafiqul Bhuyan, James Kuhle, Nuriddin Ikromov, Charles Chiemeke

American University of Kuwait, Kuwait City, Kuwait.
California State University, Sacramento, USA.

Using mean-variance utility function analysis with various degrees of risk aversion, this research examines the impact of Real Estate Investment Trusts (REITs) in creating optimal portfolios. It also examines and develops a sensitivity analysis for differential risk premiums in REIT stocks and the effect in determining an optimal portfolio mix by applying mean variance analysis. When the combined risk premium of REITs and stocks is 1.5%, we find investors with risk aversion between 1 and 6 are better off investing almost entirely in REITs, short selling the bond and investing very little in stocks. Investors can benefit in the same way even when the risk premium of REITs and stock is fixed at 2.0% with risk aversion equal to between 1 and 9. However, when the risk premium of REITs and stock is fixed at 2.5%, the investor’s risk aversion factor is irrelevant, and it suggests investors should short sell the bond and invest mostly in REITs. The marginal effect of changes in (portfolio returns) rR on the optimal portfolio weights in REITs is observed to have a sharp decline when risk aversion is increased. However, the impact of that change in the REIT-Stock correlation is non-existent as the optimal weight in REITs is increased. In addition, there is little obvious change when the risk aversion is increased. Therefore, the change of weights in REITs in the optimal portfolio is more significant than the correlation between REITs and stock performance. Results also indicate that the investor should consider how to maximize their return using various levels of risk aversion and not by using the correlation between stock and REITs.

Mean-Variance Utility; Optimal Portfolio; Risk Aversion; Correlation; REITs

R. Bhuyan, J. Kuhle, N. Ikromov and C. Chiemeke, "Optimal Portfolio Allocation among REITs, Stocks, and Long-Term Bonds: An Empirical Analysis of US Financial Markets," Journal of Mathematical Finance, Vol. 4 No. 2, 2014, pp. 104-112. doi: 10.4236/jmf.2014.42010.