Hedge  Fund  Profiling

Risk  profiling  of Hedge  Funds  for funds  of  funds

When managing fund of Hedge Funds or funds of funds, two complementary types of risk analysis can be run: a position-based analysis (when you know the composition of the underlying funds) and a return-based analysis (based on historical NAVs of the underlying funds). Riskdata allows you to perform both types of analysis.

If you know the composition of your underlying funds, you may model the funds by their actual investments and run your risk analysis with “full lookthrough” as if you had directly invested in the different assets. This kind of analysis can be run in Riskdata with the features mentioned in the other sections.

However, running a position-based risk analysis does not give you the whole information. Since a full lookthrough analysis gives you a snapshot of risk at a given moment, two effects are neglected:

  • The behaviour of the Hedge Fund manager:

    To measure your risk, you need to know typically how the manager behaves when markets are very jittery. On a return-based analysis, the historical NAVs and its correlation with market give you clues on the hedge fund manager behaviour, both in normal and extreme market conditions. You cannot have such information with a position-based analysis.

  • The horizon of risk in combination with the turn-over of the fund:

    If you are interested in your long-term risk and if the turn-over of the fund you invest in is high, position-based analysis will give you very poor information.


Riskdata calculates beta, sensitivity and VaR for the whole fund of hedge funds but also the risk contribution of each hedge fund or by hedge fund strategy.


Whatever the fund and its strategy, the risk profile will automatically scan the same set of global risk factors, minimizing the risk of reaching a wrong style assessment. This is especially useful when running due diligence on a new investment, to make sure the risk profile is consistent with the announced style.


For each risk factor, four different correlations are computed, corresponding to four market regimes, without a priori assumptions on the fund behavior. This enables asymmetrical behavior to be detected.


For each factor, the system computes four standardized stress scenarios, based on best and worst cases of the factor, taking into account more than 30 years of data. So it offers the best hedge against “time bomb” risk (i.e. managers who appear un-risky, but are simply surfing on the latest trend and will blow up when the trend changes).