Benefits of a Tree-Based model for stock selection in a South African context

Master Thesis


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University of Cape Town

Quantitative investment practitioners typically model the performance of a stock relative to its benchmark and the stock's fundamental factors in a classical linear framework. However, these models have empirically been found to be unsuitable for capturing higher-order relationships between a stock's return relative to a benchmark and its fundamental factors. This dissertation studies the use of Classification and Regression Tree (CART) models for stock selection within the South African context, with the focus being on the period from when the Global Financial Crisis began in early 2007 until December 2012. By utilising four types of portfolios, a CART model is directly compared against two traditional linear models. It is seen that during the period focused upon, the portfolios based on the CART model deliver the best excess return and risk-adjusted return, albeit in most cases modestly above the returns delivered by the portfolios based upon the linear models. This is observed in the hedge-fund style and long-only portfolios constructed. Moreover, it is observed that the CART-based portfolios' returns are not correlated with those from the linear-model-based portfolios. This observation suggests that CART models offer an attractive option to diversify model risk within the South African context.

Includes bibliographical references.