Assessing Risk Measurement for a Portfolio of Hedge Funds

Assessing Risk Measurement for a Portfolio of Hedge Funds

Two scholars, Shubeur Rahman and Ranjan Bhaduri, have in a new paper taken a fresh look at a long-standing dilemma in the alternative investments industry.

The question is: how should investors in hedge funds (especially in a multi-asset class, multi-strategy portfolio of hedge funds) measure the market risk inherent in their portfolio? Specifically, how can they do this consistent with the fund managers’ need to keep proprietary information (their secret alpha-cooking sauce) to themselves? Rahman and Bhaduri acknowledge that managerial secrets are often “derived through much investment into research and development,” and they sympathize with the need to protect that investment.

On the other hand, investors are rightly impatient with the exposure reports that they typically receive from their managers, for several good reasons: low granularity; the use of non-standard units; the use of questionable reporting practices; lack of independent verification or oversight.

The dilemma is clear enough: investors want transparency, managers want opacity in certain critical respects, both wants are appropriate. These authors don’t see their own solution to their proposal as a brainstorm of their own, but rather as a clarification and refinement of the emerging best practices in the field.

Risk Assessment Units

Let us focus for a moment on the issue of non-standard units in risk assessment, mentioned above. Rahman and Bhaduri explain for example that a fixed income fund manager might report the dollar value of a one-basis point change in interest rates (DV01), or might report risk as exposure in 10-year and five-year equivalents, or might “provide partial DV01s of the portfolio to show the exposure to different parts of the yield curve.” Or sometimes managers might do none of these, simply citing proprietary methodology in the computation of a preferred risk metric. But even aside from that pure “trust us” approach, the presence of different units of risk management even within a single well-defined asset class adds an extra layer of complexity to the investor’s evaluation of its own portfolio, an act of layering that should be discouraged.

The Solution

The potential solution to the underlying dilemma involves the creation of a standard data flow from the prime broker to the investor. Position-level data should flow routinely from the prime broke to an independent administrator who will screen it and then relay it to an independent risk data aggregator, (an online platform) who will verify it and obtain approvals from the management (allow the veto of proprietary material) and who will make the filtered data available to the investors.

The fund administrators, as part of their screening, could standardize the units of risk assessment as discussed above. Rahman and Bhaduri suggest the Open Protocol Enabling Risk Aggregation (OPERA) guidelines, adumbrated by the Hedge Fund Standards Board, as a “good starting point for reporting standardizations,” though more work—beyond that starting point—will need to be done.

As to the aggregators, these authors observe that third-party online platforms for this purpose “are a growing area of the fintech space” which can control both the granularity of the data and the analytics available to the users.  These platforms benefit management because they constitute a centralized depository for data, (for investors who can log on and off at their own convenience) which managers prefer to needing to forward the data to multiple investors.

Typically, the analytics available to a investor through such a system would entail “determining aggregate exposures to asset classes, sectors, geographies, and portfolio sensitivities to various risk factors, such as equities, interest rates, credit spreads, performing scenario stress tests, and quantitative risk metrics (VaR, factor exposures).”

To Commingle, or Not?

Rahman and Bhaduri also hope to see increasing use over time of underlying investment structures such as single investor funds or separately managed accounts. An SMA gives the investor operational control and helps protect against Madoff-style fraud. It also protects, or at east mitigates against, less dramatic failures than the Madoff-esque: it can mitigate concentration risk strategy drift, and style drift.

The authors acknowledge that, though there may yet be a lot of room for the growth of SIFs and SMAs, the “commingled fund structure will continue to be appropriate for many investments.”

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