No abstract

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.

During the last four decades Data Envelopment Analysis (DEA) has attracted considerable attention in the OR community. Using DEA, the efficiency frontier is constructed based on assumptions concerning the production possibility set rather than a priori defining a functional relationship between inputs and outputs. In this contribution, we propose an algorithm to visualize the efficiency surface in a 3D diagram and to extract isoquants from the efficient hull based on different RTS assumptions which might be particularly helpful for presentation purposes. In doing so, we extend the existing literature which has concentrated on the visualization of production frontiers in 2D diagrams to the visualization of efficient rather than fully efficient hulls in 3D diagrams. Displaying a fully efficient hull, however, does not reflect all properties of the production possibility set as weakly efficient frontier segments are missing.