Portfolio Optimisation: a Bayesian Model Averaging approach
This 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 a...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2016
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| Online Access: | https://eprints.nottingham.ac.uk/36649/ |
| _version_ | 1848795322196688896 |
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| author | Hart, Adao Dante |
| author_facet | Hart, Adao Dante |
| author_sort | Hart, Adao Dante |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This 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. |
| first_indexed | 2025-11-14T19:30:15Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-36649 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:30:15Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-366492017-10-19T17:03:50Z https://eprints.nottingham.ac.uk/36649/ Portfolio Optimisation: a Bayesian Model Averaging approach Hart, Adao Dante This 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. 2016-09-14 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/36649/2/Diss.pdf Hart, Adao Dante (2016) Portfolio Optimisation: a Bayesian Model Averaging approach. [Dissertation (University of Nottingham only)] |
| spellingShingle | Hart, Adao Dante Portfolio Optimisation: a Bayesian Model Averaging approach |
| title | Portfolio Optimisation: a Bayesian Model Averaging approach |
| title_full | Portfolio Optimisation: a Bayesian Model Averaging approach |
| title_fullStr | Portfolio Optimisation: a Bayesian Model Averaging approach |
| title_full_unstemmed | Portfolio Optimisation: a Bayesian Model Averaging approach |
| title_short | Portfolio Optimisation: a Bayesian Model Averaging approach |
| title_sort | portfolio optimisation: a bayesian model averaging approach |
| url | https://eprints.nottingham.ac.uk/36649/ |