Madoff: A Tale of Two Funds

A quantitative analysis of a Madoff hedge fund reveals a striking similarity with another well-known case of fraud

December 04, 2008


Now that the news of Madoff’s $50B Ponzi scheme is on the front pages of news media around the world, the investment community is scratching their heads and trying to understand how this could have happened. With all the advances in academic research, investment technology and risk management tools it seems impossible to pull off an enterprise of such dimensions. The truth is that investors often prefer to ignore red flags and forgo analytical tools and techniques specifically designed to protect them from such a fraud. In 2006, at the request of a hedge fund manager, MPI performed a returns-based quantitative analysis of one of Madoff’s funds and came to the conclusion that, most likely, the returns were not real. Moreover, in trying to explain the strategy we discovered that the fund’s return pattern resembled that of a proven fraud case – the Bayou fund. This research article follows the footsteps of our 2006 study.

Returns-Based Forensics

Since 1992 returns-based style analysis (“RBSA”) tools have become firmly entrenched in the investment due diligence process on the traditional side of the industry. Institutional investors are presented with choices either of fully trusting portfolio managers or of performing tests to understand whether the manager’s stories matched the results. Up until the early 90’s this was a formidable and expensive exercise requiring the help of consultants or of investing heavily in holdingsbased analytics technology and associated infrastructure to perform a laborious analysis of the portfolio’s entire holdings history. With the advent of RBSA the process of reconciling performance with the stated management strategy became quick, inexpensive and very accurate.

This methodology gained widespread acceptance within the traditional side of the industry and provided investors with inexpensive and effective means to understand inner workings of investment products by using only performance data. It is worth mentioning that such tools are used alongside holdings-based analytics as it is a known that holdings may not be able to tell the whole story. This is because portfolio managers frequently use “window dressing,” use complex derivative strategies such as “portable alpha,” which carry heavy risks, and, finally, may not provide correct and full position information. The idea behind the returns-based approach is relatively simple. On one hand there is a holding-based story describing the investment strategy and the instruments used. On the other hand there’s a track record–a stream of monthly investment returns–that can often be closely mimicked by finding a combination of passive factors or indices that best explain the return movements. If the dynamics of factor/index exposures agree with the information derived from holdings, it reinforces the confidence in the strategy. However, if there’s a notable discrepancy, it enables an investor to question the manager’s story.

Until recently, the applicability of returns-based analysis to alternative investment products was relatively limited. As compared with traditional investments, hedge funds may take significant short positions, employ leverage, and engage in very rapid, almost instantaneous, strategy changes with the help of derivatives. Unfortunately, traditional “window-based” regression techniques are limited in their ability to handle these complex investments. To address the limitations of traditional RBSA in dealing with hedge funds, a new methodology, Dynamic Style Analysis (DSA), was specifically developed to improve the returns-based analysis of hedge funds. For our analysis below we use MPI Stylus application utilizing DSA technique.

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