Abstract
This project explored the Black-Litterman framework to construct a portfolio of stocks listed in the S&P 100 index, and tracked the performance of the efficient portfolio against the S&P 100 index. Thirteen technical indicators (viz. RSI, Bollinger Bands, MACD etc.) were used to incorporate the investor’s personal views into the Bayesian framework. Performance of an equally-weighted linking matrix was compared against the performance of a distributed linking matrix in the training period of January 2009 to December 2013, wherein the constructed portfolios minimized Expected Shortfall under the said probabilistic model. Excluding transaction costs, the resulting optimized portfolio outperformed the benchmark during the testing period of January 2014 to December 2018 on both nominal and risk-adjusted basis as measured by overall performance and Sharpe ratio.
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