With the aim of optimally reaping factor premia, the thesis utilises parametric portfolio polices to inquire about the merits of timing factors based on time-series predictors and tilting factors conditioned on cross-sectional characteristics. To investigate this issue, the thesis introduces an innovative two-step procedure that effectively tames the factor zoo by capitalising on the traditional asset pricing framework to identify uniquely priced factors and evaluate the economic value from these factors in using factor timing and factor tilting strategies.
The results document compelling evidence on the overall ability of time-series predictors and cross-sectional characteristics to time and tilt factor premia such that the corresponding active portfolio performance dominates its otherwise equivalent passive portfolio. In terms of investment performance, factor timing and factor tilting significantly outperform the passive portfolio both before and after transaction costs.
While the analysis shows that outperformance is non-negligible, transaction costs do erode a substantial part of the actively generated returns, and the benefit of timing and tilting is specific to the predictors and characteristics selected. Hence, this paper refrains from drawing sensational conclusions about active factor allocation strategies being inherently superior to a passive, diversified factor strategy. Instead, it acknowledges the need for scrutiny in first of all identifying systematic risk factors, due to the exploding factor zoo, and secondly, it stresses the difficulties associated with finding important predictors and tilt characteristics that can harvest the factor premia. Therefore, this thesis provides a breath of optimism about active factor allocation by documenting its potential benefit for significant outperformance relative to a passive factor strategy, but appreciates, this is not an easy task.
|Educations||MSc in Applied Economics and Finance, (Graduate Programme) Final Thesis|
|Number of pages||145|