A Japanese hedge fund company some are calling “the Japanese Bernard Madoff” seems to be reaffirming the maxim that if returns are too good to be true, there probably is something wrong.
According to initial media reports, AIJ Investment Advisors Co. claimed to generate 241 percent for investors since 2002, despite a 2009 industry newsletter warning that the fund’s returns were “unnaturally stable.”
Vanderbilt University finance professor Nicolas Bollen, an internationally recognized expert on hedge-fund fraud, says these types of cautionary flags should not be ignored.
“[rquote]My research on hedge funds shows that this type of early warning based on suspicious patterns in returns is a reliable predictor of the risk of fraud[/rquote],” Bollen said. “I show that funds with certain performance properties, such as returns that are statically unrelated to benchmarks and returns that are rarely negative, are more likely to be subsequently charged with misreporting by the SEC than other funds.”
In addition, Bollen’s latest work finds that those hedge funds that generate the most unique returns – a characteristic prized by investors looking for truly alternative strategies – contain higher risks, making them most likely to collapse.
CATCHING HEDGE FUND CHEATERS
Bollen’s earlier research identified five ways to monitor potentially fraudulent hedge funds:
1. A kink in the fund’s distribution of returns at zero
A statistical test will show a lack of smoothness – a kink – in a hedge fund’s distribution of reported returns at zero. This may indicate an effort to avoid reporting a loss by inflating returns in one month, then later reversing the overstatements. When calculating returns on a bimonthly basis, the study found that this kink disappears.
2. A low correlation with other assets
Hedge fund returns should be correlated with a set of investment “style factors,” which researchers developed to mimic well-known hedge fund trading strategies. A low degree of correlation could be the result of a hedge fund actually making good on its promise to deliver unique returns. However, Bollen argues that if no reliable correlation exists, it is likely that the hedge fund returns are distorted, perhaps in an effort to mask risk, or, as in the case of Madoff, because they were being fabricated.
3. Artificially smooth returns
Returns that show a low level of volatility and a positive serial correlation could be the result of hedge fund managers purposely smoothing returns by reporting moving averages. Research has shown that moving averages feature lower volatility than raw observations, and will possess serial correlation even when raw observations have none.
4. Losses being reported differently than gains
When the serial correlation is conditional on a particular variable, it may point to a hedge fund manager’s desire to smooth losses by delaying reports of poor performance, while fully reporting gains when they occur in hopes of winning investor capital.
5. Poor data quality
Portfolios can be analyzed for “man-made” data patterns that include characteristics such as too many returns exactly equal to zero, too few unique returns, too long a string of identical returns and an extremely low percentage of negative returns. On the last point, the authors say there would naturally be very few reported losses if returns were being fabricated, such as in a Ponzi scheme.
A link to the research paper Predicting Hedge Fund Fraud with Performance Flags can be found at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1569626.
Written by Ryan Underwood and Amy Wolf.