Systematic asset allocation using flexible views for South African markets
| dc.contributor.advisor | Gebbie, Timothy | |
| dc.contributor.author | Sebastian, Ponni | |
| dc.date.accessioned | 2022-03-15T11:54:26Z | |
| dc.date.available | 2022-03-15T11:54:26Z | |
| dc.date.issued | 2021 | |
| dc.date.updated | 2022-03-15T11:18:17Z | |
| dc.description.abstract | We implement a systematic asset allocation model using the Historical Simulation with Flexible Probabilities (HS-FP) framework developed by Meucci [142, 144, 145]. The HS-FP framework is a flexible non-parametric estimation approach that considers future asset class behavior to be conditional on time and market environments, and derives a forward-looking distribution that is consistent with this view while remaining as close as possible to the prior distribution. The framework derives the forward-looking distribution by applying unequal time and state conditioned probabilities to historical observations of asset class returns. This is achieved using relative entropy to find estimates with the least distortion to the prior distribution. Here, we use the HS-FP framework on South African financial market data for asset allocation purposes; by estimating expected returns, correlations and volatilities that are better represented through the measured market cycle. We demonstrate a range of state variables that can be useful towards understanding market environments. Concretely, we compare the out-of-sample performance for a specific configuration of the HS-FP model relative to classic Mean Variance Optimization(MVO) and Equally Weighted (EW) benchmark models. The framework displays low probability of backtest overfitting and the out-of-sample net returns and Sharpe ratio point estimates of the HS-FP model outperforms the benchmark models. However, the results are inconsistent when training windows are varied, the Sharpe ratio is seen to be inflated, and the method does not demonstrate statistically significant outperformance on a gross and net basis. | |
| dc.identifier.apacitation | Sebastian, P. (2021). <i>Systematic asset allocation using flexible views for South African markets</i>. (). ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/36094 | en_ZA |
| dc.identifier.chicagocitation | Sebastian, Ponni. <i>"Systematic asset allocation using flexible views for South African markets."</i> ., ,Faculty of Science ,Department of Statistical Sciences, 2021. http://hdl.handle.net/11427/36094 | en_ZA |
| dc.identifier.citation | Sebastian, P. 2021. Systematic asset allocation using flexible views for South African markets. . ,Faculty of Science ,Department of Statistical Sciences. http://hdl.handle.net/11427/36094 | en_ZA |
| dc.identifier.ris | TY - Master Thesis AU - Sebastian, Ponni AB - We implement a systematic asset allocation model using the Historical Simulation with Flexible Probabilities (HS-FP) framework developed by Meucci [142, 144, 145]. The HS-FP framework is a flexible non-parametric estimation approach that considers future asset class behavior to be conditional on time and market environments, and derives a forward-looking distribution that is consistent with this view while remaining as close as possible to the prior distribution. The framework derives the forward-looking distribution by applying unequal time and state conditioned probabilities to historical observations of asset class returns. This is achieved using relative entropy to find estimates with the least distortion to the prior distribution. Here, we use the HS-FP framework on South African financial market data for asset allocation purposes; by estimating expected returns, correlations and volatilities that are better represented through the measured market cycle. We demonstrate a range of state variables that can be useful towards understanding market environments. Concretely, we compare the out-of-sample performance for a specific configuration of the HS-FP model relative to classic Mean Variance Optimization(MVO) and Equally Weighted (EW) benchmark models. The framework displays low probability of backtest overfitting and the out-of-sample net returns and Sharpe ratio point estimates of the HS-FP model outperforms the benchmark models. However, the results are inconsistent when training windows are varied, the Sharpe ratio is seen to be inflated, and the method does not demonstrate statistically significant outperformance on a gross and net basis. DA - 2021_ DB - OpenUCT DP - University of Cape Town KW - Statistical Sciences LK - https://open.uct.ac.za PY - 2021 T1 - Systematic asset allocation using flexible views for South African markets TI - Systematic asset allocation using flexible views for South African markets UR - http://hdl.handle.net/11427/36094 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/36094 | |
| dc.identifier.vancouvercitation | Sebastian P. Systematic asset allocation using flexible views for South African markets. []. ,Faculty of Science ,Department of Statistical Sciences, 2021 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/36094 | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Statistical Sciences | |
| dc.publisher.faculty | Faculty of Science | |
| dc.subject | Statistical Sciences | |
| dc.title | Systematic asset allocation using flexible views for South African markets | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationlevel | MSc |