A risk-budgeting framework for the combination of factor equity portfolios - Wegener, Fergus (Division of Actuarial Science, 2016)
This dissertation examines a risk-budgeting approach to the construction of factor equity portfolios, proposed by de Carvalho et al. (2014). The approach begins with the construction of active-weighted portfolios with exposure to factors that historically have been linked to excess returns in the market. These factor portfolios are then combined using a risk-budgeting approach. Implied stock-level returns are then estimated using this combined active allocation, and a further optimisation allows for the incorporation of specific investor constraints. The framework constitutes a risk-based approach to portfolio construction in the sense that no direct estimation of expected stock returns is required, but is dependent on a robust estimation of the covariance structure of stock returns. The framework is first evaluated in the context of a simulation study. This section provided confirmation for the risk model estimation methodology used, as well as insight into the intricacies of the framework, in an environment where the underlying structure of data was known. The framework is useful for investors who wish to combine a set of active portfolios, by controlling the allocation of risk, and understanding the exposure of the final portfolio to each of the factor portfolio components. Based on the findings of the simulation study and a back-test of the framework on JSE data, it was found that at the risk-budgeting juncture, the level of prior information imposed (with regard to the performance of factor portfolios) has a significant impact on the performance of final portfolios. In addition, the application of investor constraints, such as long-only and absolute weight limits, ultimately hinder the investor's ability to retain the views taken on in the factor portfolio components. Furthermore, due to significant discrepancies in ex-ante and ex-post tracking error risk measurement, the use of alternative, or adjusted, risk measures is recommended.