It has been suggested that the Kalman filter technique may be used to improve the quality of hedge fund replication, compared to existing replication techniques. This study uses the Kalman filter technique, along with three variations of the rolling-window regression technique, to create clones which attempt to replicate the returns of various categories of hedge fund indices. These clones are created over several scenarios and are used to compare the ability of the Kalman filter and rolling-window regression techniques. The clones are constructed using South African specific asset class and investment style factors. This study finds that the Kalman filter does not provide the expected improvement in replication ability over the rolling-window regression, for the hedge fund indices analysed. The competing techniques appear to each be better suited to replicating different hedge fund index strategies and may, therefore, be used in combination. While some of the hedge fund clones offer desirable risk characteristics, they offer lower mean returns and underperform their indices in most periods. As such, the hedge fund clones constructed in this study require further refinement and are not yet equipped for use in practice.
Noakes, M. 2016. Factor-based replication of hedge funds using a state space model. University of Cape Town.