| dc.description.abstract | This thesis applies the Black Litterman model to a defined universe on the S&P 500 index to investigate whether the asset allocation predicted through active management will yield increased risk-adjusted returns and we aim to answer the research question:
Will the asset allocation predicted by the Black Litterman model on the S&P 500 index yield superior risk-adjusted returns?
The Black Litterman model allows us to implement our views about the future and reallocates the weights of the portfolio. Our views will be based on the average stock recommendations from brokers and the spread to the actual stock prices. Two Black Litterman portfolios are constructed, with and without short positions. For comparison, we constructed four other fictive reference portfolios based on different management strategies.
We find that the Black Litterman model without short positions outperformed all reference portfolios including the benchmark when considering a risk-adjusted return. It yielded a risk-adjusted return over the benchmark of 2.8% as well as a 43% decrease in the standard deviation of 9.60% compared to the benchmark of 16.82%. The management strategy also outperformed all reference portfolios with an annualized Sharpe-ratio of 0.97 compared to the benchmark of 0.74. Additionally, it was better diversified with an annualized Treynor-ratio of 0.14 versus the benchmarks of 0.13.
However, because our research is limited in that we constrain our investment universe and do not include transaction costs we cannot conclude that the asset allocation predicted by the Black Litterman model will yield increased risk-adjusted returns in a real investment environment. | |