Interaction effects within factor investing in a South African context
The notion of portfolio tilting towards fundamental factors has been the subject of many empirical studies over the last few decades. With this being said, there is limited literature on the interaction effects between these individual factors. This dissertation focuses specifically on quality, valu...
Main Author: | |
---|---|
Other Authors: | |
Format: | Dissertation |
Language: | English |
Published: |
University of Cape Town
2017
|
Subjects: | |
Online Access: | http://hdl.handle.net/11427/25531 |
id |
ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-25531 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-255312020-10-06T05:11:24Z Interaction effects within factor investing in a South African context Varejes, Luc Mohamed, Obeid Mathematical Finance The notion of portfolio tilting towards fundamental factors has been the subject of many empirical studies over the last few decades. With this being said, there is limited literature on the interaction effects between these individual factors. This dissertation focuses specifically on quality, value, low volatility and momentum and determines which factors have the largest impact on portfolio return. In addition to testing these single factor portfolios, the various interaction effects between the individual factors are investigated. This framework is divided into two parts. The first, is an empirical study on the JSE Top 100 over the 15 year period beginning September 2001 and ending September 2016. Quarterly and monthly rebalancing as well as transaction costs of 100 basis points (per trade) have been employed to mimic realistic investment management. Much of the framework used to incorporate these factors is adapted from Bender and Wang (2016) who tested these interactions on the S&P 500. The second, involves the construction of a controlled market model in an attempt to provide mathematical justification to the framework. The controlled model simulates stock price paths, in a Mil'shtein (1974) fashion, using Geometric Brownian Motion with a stochastic alpha component added to the drift. Factors are simulated randomly using correlated uniform distributions. The controlled model uses realistic market parameters and constructs the factor portfolio in the same manner as the empirical study. 2017-10-04T14:27:42Z 2017-10-04T14:27:42Z 2017 Master Thesis Masters MPhil http://hdl.handle.net/11427/25531 eng application/pdf University of Cape Town Faculty of Commerce Division of Actuarial Science |
collection |
NDLTD |
language |
English |
format |
Dissertation |
sources |
NDLTD |
topic |
Mathematical Finance |
spellingShingle |
Mathematical Finance Varejes, Luc Interaction effects within factor investing in a South African context |
description |
The notion of portfolio tilting towards fundamental factors has been the subject of many empirical studies over the last few decades. With this being said, there is limited literature on the interaction effects between these individual factors. This dissertation focuses specifically on quality, value, low volatility and momentum and determines which factors have the largest impact on portfolio return. In addition to testing these single factor portfolios, the various interaction effects between the individual factors are investigated. This framework is divided into two parts. The first, is an empirical study on the JSE Top 100 over the 15 year period beginning September 2001 and ending September 2016. Quarterly and monthly rebalancing as well as transaction costs of 100 basis points (per trade) have been employed to mimic realistic investment management. Much of the framework used to incorporate these factors is adapted from Bender and Wang (2016) who tested these interactions on the S&P 500. The second, involves the construction of a controlled market model in an attempt to provide mathematical justification to the framework. The controlled model simulates stock price paths, in a Mil'shtein (1974) fashion, using Geometric Brownian Motion with a stochastic alpha component added to the drift. Factors are simulated randomly using correlated uniform distributions. The controlled model uses realistic market parameters and constructs the factor portfolio in the same manner as the empirical study. |
author2 |
Mohamed, Obeid |
author_facet |
Mohamed, Obeid Varejes, Luc |
author |
Varejes, Luc |
author_sort |
Varejes, Luc |
title |
Interaction effects within factor investing in a South African context |
title_short |
Interaction effects within factor investing in a South African context |
title_full |
Interaction effects within factor investing in a South African context |
title_fullStr |
Interaction effects within factor investing in a South African context |
title_full_unstemmed |
Interaction effects within factor investing in a South African context |
title_sort |
interaction effects within factor investing in a south african context |
publisher |
University of Cape Town |
publishDate |
2017 |
url |
http://hdl.handle.net/11427/25531 |
work_keys_str_mv |
AT varejesluc interactioneffectswithinfactorinvestinginasouthafricancontext |
_version_ |
1719349299338280960 |