On the efficiency of Risk measures for Funds of Hedge Funds

The hedge fund industry has experienced some very troublesome periods in
the recent past. In this study, we test the efficiency of simple and advanced risk measures
during these difficult market periods according to the Basel II requirements. We
concentrate on Fund of Hedge Fund (FoHF) data, as some studies propose that they
suffer least from database and measurement biases, and are therefore likely to yield the
most representative results compared to other alternative investment data. We examine
model stability and risk measure efficiency using unconditional and conditional GMMbased
and likelihood ratio tests, as well as independence tests.We find that model stability is
very dependent on the successful specification of autoregressive and volatility models. In
addition, custom quantile estimation is less susceptible to misspecification than volatility
models. Further, we assess the hypothesis of market efficiency for the special case of FoHF.
Finally, we find evidence of different level of managerial skill in terms of asset choice,
allocation and market timing.