“The reality is that what an investor 'knows' about the future is small compared to what he can’t know. This simple concept is so important it is worth repeating. What we know about the future is tiny compared to what we do not—and in all likelihood cannot—know.” -Mark Finn
Mark T. Finn’s one big thing is investor reliance on past performance. He wrote, “Our observation is that past performance dominates investors’ decision processes so much that we contend that past performance data may be the most misused information in the investment business.”
Since 1986, Finn has been the Chairman and CEO of Vantage Consulting Group. According to his biographic profile on the firm’s website, he consults with large pension funds and has served with the Virginia Retirement System, Alaska State Retirement System and the Chicago Mercantile Exchange’s Advisory Committee on Managed Futures. Most recently, he has been an independent director on the Legg Mason Partners Fund Board.
John Mauldin thought highly of Finn and made him one of the dozen contributors to his 2006 book, “Just One Thing: Twelve of the World's Best Investors Reveal the One Strategy You Can't Overlook.”
Finn titled his chapter, “The Triumph of Hope Over Long-Run Experience: Using Past Returns to Predict Future Performance of a Money Manager,” which gets us back to the original proposition: Why do investors rely so heavily on past performance when choosing a fund or fund manager?
While the article seems slanted to serve big institutional investors, there are lessons here for individual investors as well.
Noise in the air
According to the author, noise in the investing market is analogous to the engineering idea of the “signal to noise ratio.” In the case of the stock market, he suggested there is much more noise than signal. He attributes the noise to three types of risk:
- Systemic risk, or information about what happens in the overall stock market.
- Residual common factor risk refers to whatever is going on in subgroups such as industries.
- Residual-specific risk, or whatever occurs with any specific stock.
Investors and academics have made many attempts to address the noise problem. For example, in the 1970s, the concept of “beta” was developed. It measures how sensitive an investment is in relation to an appropriate benchmark, but it could not solve the problem. Nor could the Sharpe ratio, which shows the relationship between risk and returns.
The problem, according to Finn, is this: “At the end of the day, what we find is that it takes an inordinately long time to determine if a manager’s risk adjusted returns are a reflection of skill or simply luck (noise). Using just the past few years of a manager’s returns is pointless from a statistical point of view.”
Performance
Next, the author asked if studies showed that past performance had been predictive. Overwhelmingly, the answer was no.
In addition to the noise problem, Finn cited problems with several other factors:
- Performance of the portfolio versus performance of a specific fund manager.
- Weightings of individual managers, which are unknown to investors.
- Time periods: Sometimes five- or 10-year periods do not include both bull and bear markets.
Why do investors count so much on past performance?
The author addresses the issue again, with more specifics:
- Because investors do not appreciate the level of uncertainty, and “the central role uncertainty plays in just about everything related to investing.”
- Hindsight bias, a psychological construct that leads us to believe past events were more inevitable than they actually were. We forget how much uncertainty there was previously.
- Cause and effect in the sense that we believe things are connected in a causal way when, in fact, the relationship was random.
- Human minds have information processing limitations, so we give more credence to historical performance than may be deserved.
- Accuracy of decisions does not necessarily improve with additional information (at least on a linear basis).
In winding up the section, Finn wrote, “In summary, people have great difficulty in dealing with the randomness that abounds in the real world. They want to believe the world is more predictable than it is.”
Exceptions
While the author has emphasized that past performance is a shaky foundation on which to build a future projection, he also noted there are some situations where past performance is meaningful. These are the criteria that must exist for the past to help divine the future:
- The benchmark against which a manager is judged is a good representation of the manager’s style.
- Many decisions, in many different market circumstances, are reflected in the performance record.
- At least one of these two conditions must apply: The portfolio is suitably diversified or that the manager pointed out—in advance—why her decisions would lead to outperformance.
- The environment in which the manager operated remains relatively stable, and “alpha” was large in relation to the level of diversification (“alpha” refers to a manager’s ability to generate returns in excess of what would be expected for a specific level of risk).
Given that there are four stringent criteria, these situations are likely to be quite rare.
Conclusion
There’s a standard disclaimer that goes with reports of past performance; it goes something like this: “Past performance is no guarantee of future results.” As many of us know from our investing disappointments, that is very often the hard truth.
In his chapter of “Just One Thing,” Finn explained why past performance cannot reliably predict future performance. Uncertainty about the future is always greater than our knowledge of the past. In particular, he pointed to systemic risk, residual common factor risk and residual-specific risk, along with all the randomness that exists.
And, he observed that from a statistical perspective, we would need a very long history of past performance to be able to judge a manager’s performance.
Read more here:
- Just One Thing: Work With a Set of Investing Rules
- Just One Thing: Lower Costs
- Inefficient Market Theory: Measuring the Foolishness of the Crowd
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