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.

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