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Why do you write about academic research? Why don't you provide more frequent updates about where different markets are headed?
One of our key beliefs is that rather than focusing on relative performance (versus peers or a benchmark), investors and trustees (as opposed to the investment managers they employ) should instead focus on achieving the minimum compound real portfolio return they need to realize their long-term goals. Once a long-term asset allocation policy has been established with this target real return in mind, monitoring asset class valuations and avoiding large downside losses is critically important. So too is balancing different ways to accomplish this objective, including diversification and rebalancing, the use of options, and sometimes moving into cash. Another of our key beliefs is that markets function as a complex adaptive system, in which asset classes can become substantially over and undervalued, due to the interaction of fundamental value and momentum strategies, and the underlying investor decision making on basis of a complex mix of rational, emotional and social inputs. In the constantly evolving markets that result, anyone who makes investment decisions faces an ongoing sensemaking challenge that has three parts: where to allocate scarce attention (i.e., deciding what information is valuable), explaining the meaning of this information in light of your investment goals, and predicting how the situation is likely to evolve in the future. In turn, this process of making sense of the current situation helps an investor to identify, evaluate and choose between different decision options (e.g., stay fully invested in 2007, or move out of overvalued asset classes and into cash?).
Clearly, personal experience contributes to this process. Yet over the past thirty years, we have repeatedly seen great traders and investors blow themselves up when they wrongly relied on mental or quantitative models after the system in which they had been developed had changed. That is the curse of expertise: unless it is constantly challenged and renewed, its validity will decline. So the real question becomes how to do this. There are many different approaches, including consciously broadening and trying to learn from experience (rather than simply repeating what works until it doesn't any more), learning from history, learning from simulations, learning from others (e.g., adding diversity to your group, or seeking outside forecasts in addition to your own), and learning from academic research studies (the best of which are based on practitioner experience) that offer new or updated theories. All of these provide a richer source of frameworks that an investor can use when allocating his or her attention, understanding the current situation, predicting how it will evolve in the future, identifying options, and deciding what action to take. So that's why we report on new academic research findings: because learning from them is one of the ways investors can improve their performance.
As for the frequency with which we update our views about where markets are headed, our starting point is that we are investors, not traders, and are guided more by our views about fundamental value that we are by short term changes in investor behavior that are much harder to predict (though we are strong believers that a wide divergence between fundamental valuation indicators and current market momentum often marks an impending turning point). As Ben Graham famously wrote, "in the short-run, the market is a voting machine - reflecting a voter registration test that requires only money, not intelligence or emotional stability - but in the long-run, the market is a weighing machine." In today's world of widespread internet connectivity and 24/7 news cycles, Graham's insight has never been more accurate or more important. Investors today are more interconnected and facing a much higher volume of often sensationalized data than ever before. Even a small sampling of the hourly market analysis provided on television and radio stations, to say nothing of the minute by minute analysis provided online, make it clear that many commentators make either no or only minimal effort to discriminate between the diagnostic value and reliability of each new piece of data, and instead automatically link them to short term market moves and use this dubious causal analysis to hype their importance. But let's be honest - most of these media outlets are in the business of aggregating audiences for advertisers who pay the bills. Generating high emotional energy, and indeed, a sense of urgency, is what it takes to make their business model succeed. They know that people instinctively pay attention to information with high emotional content, and readily communicated it to others. However, that is not our approach. Instead, we concentrate on fundamental asset class valuation, and decisions guided by good analysis and explicit logic. Providing our asset class valuation and economic updates just once each month quite honestly provides time for both us and our subscribers to think. To put it differently, we believe that taking the time to reflect, and publishing once a month, is critical to the quality of the insights we provide, as well as the quality of our subscribers' decision making process.
Why do you not include currencies as asset classes in your model portfolios?
While we are familiar with institutional style currency overlay programs, we decided that this approach would be "a bridge too far" for many investors, not the least because of the calculations involved. In our model portfolios, currency exposure is bound up with exposure to foreign currency denominated asset classes, all of which we use on an unhedged basis (and note that the local currency returns on commodities, timber, and uncorrelated alpha in our models all reflect the underlying return in USD, plus the exchange rate change). That said, with the recent introduction of so many currency based ETF products, we are once again re-examining this position.
Is your use of uncorrelated alpha strategies in some of your model portfolios inconsistent with your belief in passive investing?
On the surface, yes, but at a deeper level, no. At one level, multiple research studies make it clear that, after expenses and taxes, the number of active managers who can outperform a comparable index fund declines sharply with time. Other research has concluded that a substantial portion of the alpha that is actually delivered by active managers reflects luck rather than skill (see, for example, "False Discoveries in Mutual Fund Performance" by Barras, Scaillet, and Wermers), and that it is extremely difficult to distinguish between the two. It is also clear that it is easy for unscrupulous investment managers to game systems that attempt to measure alpha (see "The Hedge Fund Game: Incentives, Excess Returns and Performance Mimics" by Foster and Young). The challenges facing active managers are no doubt extremely hard. Superior investment performance results from superior forecasts, which in turn must be based on either superior information and/or superior models. We know that markets are not perfectly efficient, because superior forecasts are possible, at least during some periods. One of our core beliefs is that, like the economy, financial markets function as a complex adaptive system, in which information does not flow freely, investors are imperfectly rational, and multiple investment strategies compete and have different impacts on prices. The net result is that markets are usually in a state of disequilibrium, which is a necessary precondition for active managers to make successful forecasts. Yet the existence of disequilibrium is also the basis of our belief that asset classes can become substantially overvalued, and that investors must consequently be vigilant about avoiding large losses.
So what explains the dismal track record of many active managers? We believe four factors are involved. First, the effectiveness of superior sources of information and superior models are inevitably undermined by competitor copying (as was seen in some hedge fund strategies) or by changes in the underlying system (e.g., the passage of Regulation FD which limited analysts' private access to companies, or the globalization of financial markets). This is no different from the observation that corporate performance tends to regress toward the mean over time, and that as the time horizon lengthens, an increasing number of companies fail. Second, portfolio constraints often mean that the accurate forecasts are not fully translated into portfolio positions (e.g., U.S. mutual funds have traditionally been prevented from taking short positions).
Third, the positive returns on accurate forecasts that are implemented in a portfolio get eaten up by expenses and taxes, which also add to the size of losses caused by inaccurate forecasts. Fourth, consider the differing situations facing an active manager whose success is judged annually based on her performance versus an index benchmark, and a manager whose performance is evaluated over a multiyear time frame, based on her ability to manage a portfolio of asset class index funds to achieve a minimum long-term compound rate of return. For the first manager, both Type 1 errors (failing to buy a stock that outperforms the benchmark) and Type 2 errors (buying a stock that underperforms) detract from performance, particularly given the short performance evaluation period (which limits the ability of regression to the mean to even out the impact of different mistakes). Each year, this manager must therefore make a large number of decisions whose stakes (given the annual performance evaluation) are high. Moreover, since the annual return on the benchmark index is driven by a mix of fundamental and behavioral factors, our manager faces a complicated set of tradeoffs every time she makes one of those decisions. As Ariely, Gneezy, Loewenstein and Mazar show in "Large Stakes and Big Mistakes", this combination of complexity and high stakes can actually lead to a degradation of performance.
Now consider our second manager. For her, once the initial asset allocation is established, only Type 1 errors are critical - i.e., failure to rebalance or hedge exposure to avoid a large loss when one or more asset classes becomes severely overvalued and then crashes. However, since this rarely happens, our second manager will have ample time to make a well considered decision, without excessive pressure. Moreover, the decision to get back into an asset class after a crash is also likely to be easier, since at that point, its expected long-term return (which are what counts given her performance objective) is likely to be higher than average. In other words, even if she doesn't get back in at the bottom, regression towards the mean over time will still be working in her favor. As a result of these factors, our second manager's average decision quality, stress level and performance are likely to be different than our first manager's.
Clearly, I have just made a convincing argument for passive investing. So why do we include uncorrelated alpha strategies in some of our portfolios? There are two reasons. First, because we believe, that under certain conditions, successful active management (i.e., positive alpha after expenses and taxes) is possible, particularly for those managers who focus on continuously improving their sources of information and/or forecasting models. Second, because of the undeniable mathematical benefits of uncorrelated alpha to a portfolio, in terms of its ability to reduce the risk you must accept in order to to achieve higher long-term real return targets. That said, the relatively low maximum limits we set on our allocation to uncorrelated alpha reflects our recognition of the difficult challenges involved in consistently delivering it over long periods of time, as does our focus on minimizing fund costs (note that the mutual funds we use cost a lot less than the "2 and 20" charged by many hedge funds), and our recommendation that these funds be held in tax-advantaged accounts. Clearly, we are trying to make a tradeoff here, and reasonable people can disagree about the maximum amount we are willing to allocate to uncorrelated alpha strategies. That said, we believe the underlying logic of our argument is sound, and in the case of higher portfolio real return targets, some allocation to uncorrelated alpha strategies makes sense from a risk/return perspective.