Portfolio Optimization: A Combined Regime-Switching and Black–Litterman Model

Traditionally portfolios are optimized with the single-regime Markowitz model using the volatility as the risk measure and the historical return as the expected return. This study shows the effects that a regime-switching framework and alternative risk measures (modified value at risk and conditional value at risk) and return measures (CAPM estimates and Black–Litterman estimates) have on the asset allocation and on the absolute and relative performance of portfolios. It demonstrates that the combination of alternative risk and return measures within the regime-switching framework produces significantly better results in terms of performance and the modified Sharpe ratio. The usage of alternative risk and return measures is also shown to meet the need that asset returns very often are not distributed normally and serially correlated. To eliminate these empirical shortcomings of asset returns an unsmoothing algorithm is used in combination with the Cornish–Fisher expansion.