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A framework for regime identification and asset allocation
The purpose of this thesis is to examine a regime-based asset allocation strategy and evaluate whether accounting for regime-dependent risk and return of asset classes provides any significant improvement on portfolio performance. The South African market and economy are considered as a proxy for th...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2016
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| _version_ | 1867614493526196224 |
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| access_status_str | Open Access |
| author | Kondlo, Mpumelelo |
| author2 | Bradfield, David |
| author_browse | Bradfield, David Kondlo, Mpumelelo |
| author_facet | Bradfield, David Kondlo, Mpumelelo |
| author_sort | Kondlo, Mpumelelo |
| collection | Thesis |
| description | The purpose of this thesis is to examine a regime-based asset allocation strategy and evaluate whether accounting for regime-dependent risk and return of asset classes provides any significant improvement on portfolio performance. The South African market and economy are considered as a proxy for the analysis. Motivation of this thesis stems from the growing body of research by practitioners devoted to models that are reflective of the interdependency between financial assets and the real economy. The asset classes under consideration for the analysis are domestic and foreign cash, domestic and foreign bonds, domestic and foreign equity, inflation linked bonds, property, gold and commodities. In order to evaluate the performance of the regime-based strategy, this thesis proposes a framework based on Principal Component Analysis and Fuzzy Cluster Analysis for regime identification and asset allocation. The performance of the strategy is tested against two strategies that are not cognizant of regime changes. These are an equally weighted portfolio and a buy-and-hold strategy. Furthermore, relative performance analysis was performed by comparing the regime-based strategy proposed in this thesis against the Alexander Forbes Large Manager Watch Index. Due to data limitations, the analysis is done on an in-sample basis without an out-of-sample testing. The results from the analysis showed the extent of outperformance of the proposed regime-based strategy relative to an equally weighted strategy and a buy-and-hold strategy. These results were consistent with existing literature on regime-based strategies. Furthermore, the results provided strong motivation for the use of the regime identification framework together with tactical asset allocation proposed in this thesis. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20475 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:52:55.424Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/20475 A framework for regime identification and asset allocation Kondlo, Mpumelelo Bradfield, David Statistical Science The purpose of this thesis is to examine a regime-based asset allocation strategy and evaluate whether accounting for regime-dependent risk and return of asset classes provides any significant improvement on portfolio performance. The South African market and economy are considered as a proxy for the analysis. Motivation of this thesis stems from the growing body of research by practitioners devoted to models that are reflective of the interdependency between financial assets and the real economy. The asset classes under consideration for the analysis are domestic and foreign cash, domestic and foreign bonds, domestic and foreign equity, inflation linked bonds, property, gold and commodities. In order to evaluate the performance of the regime-based strategy, this thesis proposes a framework based on Principal Component Analysis and Fuzzy Cluster Analysis for regime identification and asset allocation. The performance of the strategy is tested against two strategies that are not cognizant of regime changes. These are an equally weighted portfolio and a buy-and-hold strategy. Furthermore, relative performance analysis was performed by comparing the regime-based strategy proposed in this thesis against the Alexander Forbes Large Manager Watch Index. Due to data limitations, the analysis is done on an in-sample basis without an out-of-sample testing. The results from the analysis showed the extent of outperformance of the proposed regime-based strategy relative to an equally weighted strategy and a buy-and-hold strategy. These results were consistent with existing literature on regime-based strategies. Furthermore, the results provided strong motivation for the use of the regime identification framework together with tactical asset allocation proposed in this thesis. 2016-07-20T06:52:16Z 2016-07-20T06:52:16Z 2016 Master Thesis Masters MSc http://hdl.handle.net/11427/20475 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Statistical Science Kondlo, Mpumelelo A framework for regime identification and asset allocation |
| thesis_degree_str | Master's |
| title | A framework for regime identification and asset allocation |
| title_full | A framework for regime identification and asset allocation |
| title_fullStr | A framework for regime identification and asset allocation |
| title_full_unstemmed | A framework for regime identification and asset allocation |
| title_short | A framework for regime identification and asset allocation |
| title_sort | framework for regime identification and asset allocation |
| topic | Statistical Science |
| url | http://hdl.handle.net/11427/20475 |
| work_keys_str_mv | AT kondlompumelelo aframeworkforregimeidentificationandassetallocation AT kondlompumelelo frameworkforregimeidentificationandassetallocation |