Whenever a new investment approach comes along, there are always risks associated with data snooping and selection bias. Even with the best thought out methods using plenty of past data, there is still some data mining involved in selecting portfolio assets, weighting methods, re-balancing intervals, etc. Just as one can never become a virgin again, so one can never unlearn all the ideas that may become embedded in an investment methodology.
So how can one minimize the risks associated with a new investment approach? The first way is to require that the method make sense. Is it in tune with the nature of the markets?
Portfolio insurance, an idea promoted by academics having little market experience, caught on briefly in the 1980s. The idea was for investors to allocate more capital to stocks as they rose on a short term basis, and pull money away from them quickly as they declined. Any experienced market practitioner knows this is a bad idea since the stock market is short-term reactionary by nature. Sure enough, portfolio insurance incurred large whipsaw losses soon after it began. Investors gave up on it right away, with nothing to show for it but losses.
Momentum, on the other hand, has always made sense. It is based on the phrase “cut your losses; let your profits run on,” coined by the famed economist David Ricardo in the 1700s. Ricardo became wealthy following his own advice. Many others, such as Livermore, Gartley, Wycoff, Darvas, and Driehaus, have done likewise over the following years. Behavioral finance has given us solid reasons why momentum works. The case for momentum is so strong that two of the fathers of modern finance, Fama and French, call momentum “the premier market anomaly” that is “above suspicion.”
The second criterion for accepting a new investment approach is robustness. One way to judge this is by a model’s complexity. Simpler is better. Fewer moving parts means fewer unanticipated consequences and less danger of model over-specification. Overfitting data by adding complexity to a model can also make it too rigid. It may then perfectly predict the past, but not the future.
Momentum, on the other hand, is pretty simple. Every approach, including momentum, must determine what assets to use and when to rebalance a portfolio. The single parameter unique to momentum is the lookback period for determining an asset’s relative strength. In 1937, using data from 1920 through 1935, Cowles and Jones found stocks that performed best over the past twelve months continued to perform best afterward. In 1967, Bob Levy came to the same conclusion using a six-month lookback window applied to stocks from 1960 through 1965. In 1993, using data from 1962 through 1989 and rigorous testing methods, Jegadeesh and Titman (J&T) reaffirmed the validity of momentum. They found the same six and twelve months look back periods to be best. Momentum is not only simple, but it has been remarkably consistent over the past seventy-five years.
The opposite problem of too much complexity is omitted variable risk. For a model to be robust, it needs to incorporate all relevant explanatory variables. As Einstein pointed out, a model should be as simple as possible, but no simpler. Perhaps the most dramatic example of omitted variable risk is the case of Long Term Capital Management (LTCM). Academics again sold the investment community on what at first appeared to be a good idea – exploiting anomalies identified through equilibrium-pricing models. The omitted variable, in this case, was potential risk from a combination of high leverage and low liquidity. By ignoring this, LTCM almost brought about a collapse of the world’s financial system.
Momentum, however, appears safe from omitted variable risk. Momentum does not depend on esoteric markets, derivatives, leverage, or anything else out of the ordinary. As I show in my latest research paper, momentum has been highly effective when applied to the world’s most liquid markets and most well-known asset classes.
Another way of judging robustness is by seeing how well an approach holds up in multiple markets, over different time periods, and with different parameter values. Risk Parity (RP) is popular based on its attractive pro-forma performance record over the past ten years. RP puts an emphasis on fixed income assets, which have done well over this period. However, it is not logical for bonds to outperform equities indefinitely since stocks are riskier than bonds and should command a positive risk premium. In line with this, RP portfolios are not as attractive when looking at pro-forma portfolios going back more than twenty years.
Momentum, on the other hand, is one of the most robust approaches in terms of its applicability and reliability. Following the 1993 seminal study by J&T, there have been nearly 400 published momentum papers, making it one of the most heavily researched finance topics over the past twenty years. Extensive academic research has shown that momentum works in virtually all markets and time periods, from Victorian ages up to the present.
The final way to judge investment worthiness is through real-time performance. This is often the primary criterion used to evaluate investments. On its own, however, it has drawbacks. First, the time to establish statistically meaningful results is longer than most people realize. Ken French has said that seventy years of past performance data may not be a sufficiently long performance record. Some analysts believe they are being diligent by requiring a one, three, or five-year real-time track record before they will consider an unfamiliar investment opportunity. However, as disclosure requirements point out, past performance may not be indicative of future results. This is especially true when dealing with shorter-term track records and complicated investment models. Success over a handful of years may still be due to chance and a favorable set of market conditions. In fact, studies show that 3 to 5 years of past performance data is mean-reverting. Assets that di especially well during that time frame are likely to disappoint going forward.
When someone questions how long momentum has been around, I point out the Cowles and Jones research findings from seventy-five years ago and the Levy results from forty-five years ago, along with the subsequent validations of their work. Their simple approaches are the underlying basis for momentum investing, even now.