Tid: 10 februari 2014 kl 15.15-16.00.Seminarierummet 3721, Institutionen för matematik, KTH, Lindstedtsvägen 25, plan 7. Karta!
Föredragshållare: Daniel Drugge
Titel: Allocation Methods for Alternative Risk Premia Strategies (Master Thesis)
Abstract Using regime switching and regression tree methods we evaluate performance in the risk premia strategies provided by Deutsche Bank and constructed from U.S. research data from the Fama French library. The regime switching method uses the Baum-Welch algorithm at its core and splits return data into a normal and a turbulent regime. Each regime is independently evaluated for risk and the estimates are then weighted together according to the expected value of the proceeding regime. The regression tree methods identify macro-economic states in which the risk premia strategies perform well or poorly in terms of the Sharpe Ratio and use these results to allocate between risk premia strategies.
The regime switching method proves to be mostly unimpressive but has its results boosted by investing less in risky assets as the probability of an upcoming turbulent regime becomes larger. This proves to be highly effective for all time periods and for both data sources. The regression tree method proves the most effective when making the assumption that we know all macro-economic data the same month as it is valid for. Since this is an unrealistic assumption the best method seems to be to evaluate the performance of the risk premia strategy using macro-economic data from the previous quarter.
|Sidansvarig: Filip Lindskog