Bias ratio
The bias ratio is an indicator used in finance to analyze the returns of investment portfolios, and in performing due diligence.
The bias ratio is a concrete metric that detects valuation bias or deliberate price manipulation of portfolio assets by a manager of a hedge fund, mutual fund or similar investment vehicle, without requiring disclosure (transparency) of the actual holdings.
This metric measures abnormalities in the distribution of returns that indicate the presence of bias in subjective pricing.
The bias ratio measures how far the returns from an investment portfolio – e.g. one managed by a hedge fund – are from an unbiased distribution.
However, if a fund smooths its returns using subjective pricing of illiquid assets the bias ratio will be higher.
The bias ratio was first defined by Adil Abdulali, a risk manager at the investment firm Protégé Partners.
[1][2] The bias ratio has since been used by a number of Risk Management professionals to spot suspicious funds that subsequently turned out to be frauds.
The most spectacular example of this was reported in the Financial Times on 22 January 2009 titled "Bias ratio seen to unmask Madoff"!
After discarding outliers, a manager sums up the relevant figures and determines the net asset value ("NAV").
The "reserve" that allows "false positives" with regularity is evident in the unusual hump at the -1.5 Standard Deviation point.
This psychology is summed up in a phrase often heard on trading desks on Wall Street, "let us take the pain now!"
More generally, financial history has several well-known examples where hiding small losses eventually led to fraud such as the Sumitomo copper affair as well as the demise of Barings Bank.
is difficult to model, behavior induced modifications manifest themselves in the shape of the return histogram around a small neighborhood of zero.
The bias ratios of market and hedge fund indices gives some insight into the natural shape of returns near zero.
Major market indices support this intuition and have bias ratios generally greater than 1.0 over long time periods.
Cash investments such as 90-day T-Bills have large bias ratios, because they generally do not experience periodic negative returns.
Consequently, the bias ratio is less reliable for the theoretic hedge fund that has an un-levered portfolio with a high cash balance.
For example, an unexpectedly high Sharpe ratio may be a flag for skeptical practitioners to detect smoothing .
Confronted with illiquid, hard to price assets, managers may use some leeway to arrive at the fund's NAV.
Both Sun Asia and Plank are emerging market hedge funds for which the author has full transparency and whose NAVs are based on objective prices.
However the two admitted frauds, namely Bayou, an Equity fund and Safe Harbor, an MBS fund (Table IV shows the critical bias ratios values for these strategies) are uniquely flagged by the bias ratio in this sample set with none of the problems of false positives suffered by the serial correlation metric.
The bias ratio's unremarkable values for market indices, adds further credence to its effectiveness in detecting fraud.
Hedge fund strategy indices cannot generate benchmark bias ratios because aggregated monthly returns mask individual manager behavior.
All else being equal, managers face the difficult pricing options outlined in the introductory remarks in non-synchronous periods, and their choices should average out in aggregate.
A sample of equity hedge funds may have bias ratios ranging from 0.3 to 3.0 with an average of 1.29 and standard deviation of 0.5.
Ideally, a Hedge Fund investor would examine the price of each individual underlying asset that comprises a manager's portfolio.
The bias ratio gives a strong indication of the presence of a) illiquid assets in a portfolio combined with b) a subjective pricing policy.
Nevertheless, the coincidence of historical blow-ups with high bias ratios encourages the diligent investor to use the tool as a warning flag to investigate the implementation of a manager's pricing policies.
