The Black-Litterman model

Abstract

The Markowitz model has two problematic tendencies; unintuitive portfolios and portfolios with high transaction costs. The Black-Litterman model was made as an improvement of the Markowitz model. It uses a Bayesian approach to combine the views of the investor with the equilibrium portfolio. The main purpose of the model is to create intuitive portfolios and limit the transaction costs. With the computer power available today, the implementation of mathematical models are an important issue. Using the programming language R, I will in this thesis look at possible ways of implementing the Black-Litterman model. Todays investment firms have different ways of expressing their views on future asset performance. A common method is to use a scorecard. It is interesting to see how the scorecards properties make simplifying conditions to the Black-Litterman model. By using both existing R packages and self-made R code, the Black and itterman model is applied to the R language to find the best approach.