Many tools for rating the performance of mutual funds and their managers rely heavily on past performance. But what about the future? Now comes a system devised by Randolph B. Cohen and Joshua D. Coval of Harvard Business School, and Lubos Pastor of the University of Chicago Graduate School of Business. At its core, the new system compares a fund manager's investments with those of other successful fund managers, making past performance less important in the rating scheme. In short, funds are rated by the company they keep. Cohen discusses the system in this e-mail interview. Read an excerpt from the Working Paper.
Ann Cullen: How is your system different than traditional mutual fund rating systems?
Cohen: Our method takes advantage of a wealth of previously unexploited information about fund holdings. Standard metrics rate funds based on past performance. Some alternative approaches have tried to make use of knowledge about the stocks a given fund holds. What is unique in our work is that in rating each fund, we look at the overlap between that fund's holdings and the holdings of every other fund. We expect a fund to do well in the future only if it holds stocks, which are primarily held by historically successful managers. So, even if your fund has a poor track record, if you hold "good" stocks—i.e., stocks that are primarily owned by top performers—you will rate high by our future-expectations measure. We also apply a technique that looks at the overlap between the trades of funds, rather than the holdings. Using this method, a fund that holds similar stocks to a successful fund, but buys them one quarter later, would not get credit for being similar to the successful fund.
Q: What was the biggest surprise to you in your research?
We expect a fund to do well in the future only if it holds stocks that are primarily held by historically successful managers.
— Randolph B. Cohen
A: The increase in precision that our method obtains compared to the standard approach was really striking to us. In many cases our approach is five to ten times more precise. In particular, our approach appears far better able to identify stock-picking ability (if it exists) among funds that started recently. This is exciting because there are good theoretical reasons to think these funds are the most likely to outperform.
Q: How should the average fund investor use your work?
A: Unfortunately the method is quite difficult to implement—it took us many months to do it properly, and it required mutual fund holdings data that costs tens of thousands of dollars (which the HBS Division of Research was kind enough to pay for). It's possible that one of the firms that rate mutual funds will adopt our approach. We'd love to work with such a service to help make this information available to investors at large.
Q: In your analysis you relied rather heavily on Spectrum and other computer-generated data tools. How has the twenty-year availability of computer generated data sets affected the way fund managers can be evaluated now and in the future? Can the data sets help fund managers make investment decisions?
A: In the last five years there has been an explosion of academic research using the holdings data, due to its becoming more accessible and affordable. I think this research has really improved our understanding of the performance of the investment management business. For example, although it is by now well known that net returns to fund investors have on average not exceeded index returns, only in recent years have holdings studies shown that the actual stock picks of fund managers have outperformed the market. It's just that fees and trading costs have more than eaten up those stock-picking profits.
Our approach appears far better able to identify stock-picking ability (if it exists) among funds that started recently.
— Randolph B. Cohen
As to the data helping managers, it depends on how they use it. The most obvious application is for managers to try to copy their more skilled colleagues. This could be an effective strategy, and lead to more efficiently priced stocks, if markets are slow to react and if managers successfully identify the right funds to follow. Since distinguishing ability from luck in investing is always a challenge, that last requirement may not be so easy to fulfill.
Q: Do you think the Web-based data input accounting standards such as XBRL would affect the fund investment strategies of fund managers in the future?
A: Historically careful analysis of corporate information on a large number of companies has required an investor (or at least the investor's organization) to master a difficult and arcane set of data-handling tools. XBRL has the potential to make security analysis more accessible. In particular, testing and implementing quantitative strategies could become much easier. That could make it tougher for quant managers by introducing more competition, or it could help them by introducing less sophisticated competition. It's too soon to say.