Using Statistical Process Control to Monitor Active Managers

Investors who are invested in (or bear responsibility for) many active portfolios face a resource allocation problem: To which products should they direct their attention and scrutiny? Ideally they will focus their attention on portfolios that appear to be in trouble, but these are not easily identified using classical methods of performance evaluation. In fact, it is often claimed that it takes forty years to determine whether an active portfolio outperforms its benchmark. The claim is fallacious. In this article, we show how a statistical process control scheme known as the CUSUM, which is closely related to Wald's [1947] Sequential Probability Ratio Test, can be used to reliably detect flat-to-the-benchmark performance in forty months, and underperformance faster still. By rapidly detecting underperformance, the CUSUM allows investors to focus their attention on potential problems before they have a serious impact on the performance of the overall portfolio. The CUSUM procedure is provably optimal: For any given rate of false alarms, no other procedure can detect underperformance faster. It is robust to the distribution of excess returns, allowing its use in almost any asset class, including equities, fixed income, currencies and hedge funds without modification, and is currently being used to monitor over $500 billion in actively managed assets.