Hedge Funds analysts

When managing 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). Quarisma Finance lets you perform both types of analysis.

Indeed, running a position-based risk analysis cannot disclose the whole information on the fund but only gives you a snapshot of the risk at a given point in time. Return-based analysis however is the method of choice in order to capture the fund manager’s behavior and the long-term risk of the fund. This is why we firmly believe that these two methodologies are complementary.

Return-based analysis

HEDGE FUND'S MANAGER BEHAVIOR

To measure your risk, you need to know typically how the manager behaves when markets are very jittery. In a return-based analysis, the historical NAVs and their correlations with the market give you clues on the hedge fund manager behavior, both in normal and extreme market conditions.

HORIZON OF RISK AND TURN OVER OF THE FUND

Return-based analysis gives you information about your long-term risk and especially if the turnover of the funds you invest in is high.

RISK CALCULATION & AGGREGATION

Quarisma Finance calculates beta, sensitivity and VaR not only at the top level of the fund of funds but also the risk contribution of each hedge fund or by hedge fund strategy.

Hedge Fund Profiling

From our desktop solution or in less than a minute on the cloud by simply copy-pasting the fund NAVs.

CHECK & MONITOR HEDGE FUND STYLES

Whatever the fund and its strategy, our risk profiling engine will automatically scan a comprehensive set of 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.

DETECTION OF ASYMMETRICAL BEHAVIOURS

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

DETECTION OF TIME BOMBS

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).