Portfolio Optimisation: a Bayesian Model Averaging approachTools Hart, Adao Dante (2016) Portfolio Optimisation: a Bayesian Model Averaging approach. [Dissertation (University of Nottingham only)]
AbstractThis paper adopts a Bayesian Model Averaging procedure to forecast excess returns. With a dataset compiling of 78 companies from the FTSE 100, we use in-sample performance to compare BMA with the Historical Expectation, and out- of-sample performance for the comparison of BMA with realized returns and the comparison with the market strategy. Our in-sample results are compared with the Historical Expectation strategy, where the Historical Expectation produces a smaller overall error and a greater overall Sharpe ratio in October 2015. For our out-of-sample results, in January 2016, our findings show that the Consumer Goods and Services industries perform better in real time with all three different portfolio choices. We show that over the period November 2015 to July 2016, the BMA portfolio choices that outperform the market strategy are the Global Minimum Variance portfolio without short sales and the Tangency portfolio.
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