Hedge Fund Performance Benchmark Targets

With the hedge fund industry growing in recognition and maturity, a demand arises for benchmarks to evaluate the performance of hedge funds to one another and to compare hedge fund performance with other asset classes. There are various third parties that have satiated the demand for hedge fund benchmarks by providing hedge fund indices. A few of them are.

• CSFB-Tremont
• Hedge Fund Research (HFR)
• Van Hedge
• Zurich Capital Markets/MAR

There is no single index for all hedge funds. Instead, the index providers create separate indices for different hedge fund strategies. This approach categorizes similar size and correlation to the market of every type of hedge fund. Additionally, new groups are introduced as hedge fund managers devise innovative trading strategies. However, the classification has its flaws as there is no industry-wide consensus on the definition of categories. Hence indices from different providers are not always comparable with one another.

Biases

Because there are not any stringent reporting requirements, there is no single centralized database for the overall performance analysis of hedge funds. Hedge funds that do submit results and are included in a database also make use of the added recognition and legitimacy to attract new investors. This gives rise to a “self-selection bias.” That is, choosing to report results to a database might be related to the fund’s performance.

Hedge fund databases also exhibit “survivorship bias” from several causes. When a database is created, it can only reflect funds that are active and not defunct. Once a fund becomes defunct, or its reports are not submitted, it is removed from an index and its associated database. Its previous returns from their final period or entire history will no longer be reported. Some index providers practice additional selection bias and will not include small or young hedge funds. Because of this selective screening, an upward performance bias on an index is formed.

In the case of End-of-Life bias, hedge funds generally stop reporting their results during the last several months of their lives. For example, Long-Term Capital Management lost 92 percent of its capital between October 1997 and October 1998. None of these negative returns were reported to the data base providers. Posthuma and van der Sluis (2003) have estimated the bias by assuming that the hedge fund has a negative return in the month after it stopped reporting.

According to their calculations, the average industry hedge fund return would be reduced by over 600 basis points per annum if the non-reported last month return was negative 50 percent for funds leaving the data base. This method of adjustment may well improve the accuracy of the various hedge fund indexes but we have chosen to avoid such ad hoc adjustments to the data for two reasons: First, it is possible that some funds stopped reporting not because they failed, but because they did not want to attract new funds. Indeed, Ackerman et al. (1999) argue that many funds with strong results stop reporting because they no longer require the services of a data vendor. Second, we prefer to rely instead on adjustments that can be documented through the use of actual reported results. We need to recognize, however, that even our adjusted return data are likely to be biased upwards.

‘Backfill bias’ happens when hedge funds provide information to the data base publishers only if they desire to do so. Mutual funds must report to regulators and investors their periodic audited returns. Hedge fund Managers often will establish a hedge fund with seed capital and begin reporting their results at some later date and only if the initial results are favorable. Moreover, the most favorable of the early results are then “backfilled” into the data base along with reports of contemporaneous results. Fortunately, data available from TASS Research, a unit of the hedge fund group Tremont Capital Management, indicate when the hedge fund began reporting.

Hence, we can examine the backfilled returns and compare them with those returns that were reported. The result should indicate the extent to which the backfilled returns are upwardly biased. On average, the backfilled returns are over 500 basis points higher than the contemporaneously reported returns. Using both a test of the difference between the means and medians, we find that the difference between the backfilled and non-backfilled returns is highly significant. The use of backfilled returns to judge the effectiveness of hedge fund management significantly biases the returns upwards.

There is a performance shortfall associated with hedge funds that are included in aggregate performance data but that are closed to new investors. Larger the fund size gets, the higher market impact costs are there in implementing trades. Because of this detracts from net returns, hedge fund managers are sometimes incentives to close such funds. Hedge fund managers have personal wealth invested in the fund, as well as strong return-related compensation from the fund. As is the case with traditional active funds, where management fees tend to be proportional to assets under management, such options are generally closed to new investors.

If closed hedge funds tend to outperform other hedge funds, then the average measured return across funds will be higher than the average return available to new investors not already enrolled in the closed funds. This creates a difference between the average return to hedge funds versus the average return available to new hedge fund investors. Hedge fund managers are usually motivated to maximise absolute returns under any market condition. Most hedge fund managers receive asymmetric incentive fees based on positive absolute returns and are not measured against the performance of passive benchmarks that represent the overall market.

The management of hedge funds is largely based on the manager’s skill and relies on the ability of active investment management to surpass the returns of passive indexing. Hedge fund managers have the independence to select from a wide range of investment techniques and assets, including long and short positions in stocks, bonds, and commodities. Leverage is commonly used to amplify the effect of investment decisions. Fund managers have the option of trading in foreign currencies and derivatives, and they also concentrate as opposed to diversify their investments in which ever country or industry they have chosen. Hedge fund managers very often invest their own money in the fund, which further aligns their personal motivation with that of outside investors.

There are some hedge funds do not hedge at all. They take advantage of the legal and compensatory structures of hedge funds to pursue desired trading strategies. In practice, a legal structure that avoids particular regulatory restrictions remains a commonality that connects all hedge funds. Hence it is possible to use their legal status as an alternative means of defining a hedge fund.

Mutual funds have only one type of performance benchmark. The fund is managed to match or excel a particular index like FTSE-100 index, S&P 500 index etc. This is a relative return target, which some hedge funds adopt as their benchmark with the intention of measuring performance. Hedge funds have another benchmark called ‘absolute return targets.’

An absolute return target is the conventional benchmark choice for hedge funds and is the opposite of relative return. It is a fixed return target and the fund is expected to match/excel it regardless of the overall market performance. Hedge fund managers use two main approaches to achieve absolute return targets: Market Timing and the Non-Directional approach.

Market Timing

This approach involves taking positions by predicting the market trend or direction. This approach usually gives high returns. An example of the hedge fund that has used this as a practice is the Quantum Fund by George Soros (speculation on the British Pound in 1992).

Non-Directional

It is a fund that eliminates some market risks, hence it can be considered non-directional, while also taking the benefit from relative price movements of assets. An example of Non-Directional is A. Winslow’s Hedge Fund.

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