Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Factor-based replication of hedge funds using a state space model
It has been suggested that the Kalman filter technique may be used to improve the quality of hedge fund replication, compared to existing replication techniques. This study uses the Kalman filter technique, along with three variations of the rolling-window regression technique, to create clones whic...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Finance and Tax
2016
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613359704113152 |
|---|---|
| access_status_str | Open Access |
| author | Noakes, Michael A |
| author2 | Van Rensburg, Paul |
| author_browse | Noakes, Michael A Van Rensburg, Paul |
| author_facet | Van Rensburg, Paul Noakes, Michael A |
| author_sort | Noakes, Michael A |
| collection | Thesis |
| description | It has been suggested that the Kalman filter technique may be used to improve the quality of hedge fund replication, compared to existing replication techniques. This study uses the Kalman filter technique, along with three variations of the rolling-window regression technique, to create clones which attempt to replicate the returns of various categories of hedge fund indices. These clones are created over several scenarios and are used to compare the ability of the Kalman filter and rolling-window regression techniques. The clones are constructed using South African specific asset class and investment style factors. This study finds that the Kalman filter does not provide the expected improvement in replication ability over the rolling-window regression, for the hedge fund indices analysed. The competing techniques appear to each be better suited to replicating different hedge fund index strategies and may, therefore, be used in combination. While some of the hedge fund clones offer desirable risk characteristics, they offer lower mean returns and underperform their indices in most periods. As such, the hedge fund clones constructed in this study require further refinement and are not yet equipped for use in practice. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/21753 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:54.127Z |
| 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 Finance and Tax |
| publisherStr | Department of Finance and Tax |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/21753 Factor-based replication of hedge funds using a state space model Noakes, Michael A Van Rensburg, Paul Investment Management It has been suggested that the Kalman filter technique may be used to improve the quality of hedge fund replication, compared to existing replication techniques. This study uses the Kalman filter technique, along with three variations of the rolling-window regression technique, to create clones which attempt to replicate the returns of various categories of hedge fund indices. These clones are created over several scenarios and are used to compare the ability of the Kalman filter and rolling-window regression techniques. The clones are constructed using South African specific asset class and investment style factors. This study finds that the Kalman filter does not provide the expected improvement in replication ability over the rolling-window regression, for the hedge fund indices analysed. The competing techniques appear to each be better suited to replicating different hedge fund index strategies and may, therefore, be used in combination. While some of the hedge fund clones offer desirable risk characteristics, they offer lower mean returns and underperform their indices in most periods. As such, the hedge fund clones constructed in this study require further refinement and are not yet equipped for use in practice. 2016-09-14T12:50:50Z 2016-09-14T12:50:50Z 2016 Master Thesis Masters MCom http://hdl.handle.net/11427/21753 eng application/pdf Department of Finance and Tax Faculty of Commerce University of Cape Town |
| spellingShingle | Investment Management Noakes, Michael A Factor-based replication of hedge funds using a state space model |
| thesis_degree_str | Master's |
| title | Factor-based replication of hedge funds using a state space model |
| title_full | Factor-based replication of hedge funds using a state space model |
| title_fullStr | Factor-based replication of hedge funds using a state space model |
| title_full_unstemmed | Factor-based replication of hedge funds using a state space model |
| title_short | Factor-based replication of hedge funds using a state space model |
| title_sort | factor based replication of hedge funds using a state space model |
| topic | Investment Management |
| url | http://hdl.handle.net/11427/21753 |
| work_keys_str_mv | AT noakesmichaela factorbasedreplicationofhedgefundsusingastatespacemodel |