Quantitative Forecast Model for the Application of the Black-Litterman Approach

The estimation of expected security returns is one of the major tasks for the practical implementationof the Markowitz portfolio optimization. Against this background, in 1992 Black and Littermandeveloped an approach based on (theoretically established) expected equilibrium returns whichaccounts for subjective investors’ views as well. In contrast to historical estimated returns, which leadto extreme asset weights within the Markowitz optimization, the Black-Litterman model generally resultsin balanced portfolio weights. However, the existence of investors’ views is crucial for the Black-Litterman model and with absent views no active portfolio management is possible. Moreover, problemswith the implementation of the model arise, as analysts’ forecasts are typically not available inthe way they are needed for the Black-Litterman-approach. In this context we present how analysts’dividend forecasts can be used to determine an a-priori-estimation of the expected returns and howthey can be integrated into the Black-Litterman model. For this purpose, confidences of the investors’views are determined from the number of analysts’ forecasts as well as from a Monte-Carlo simulation.After introducing our two methods of view generation, we examine the effects of the Black-Littermanapproach on portfolio weights in an empirical study. Finally, the performance of the Black-Littermanmodel is compared to alternative portfolio allocation strategies in an out-of-sample study.