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Developing Better Foresight
One of the most frequently heard comments about the crash of 2008 is, "I didn't see it coming." This raises a critical question: How can you improve the accuracy of your financial forecasts, or, more broadly, the quality of your foresight?
We believe the answer to this question begins with understanding the nature of the system whose behavior we are trying to predict. At one extreme, physical systems are characterized by relationships defined by the laws of physics and chemistry that are stable over time. It should therefore be possible to use a single model to forecast the behavior of such a system with a high level of confidence over both short and long time horizons. Moreover, knowledge of this system's past behavior can be used to accurately specify the values for the variables used to model its future behavior.
At the other extreme, social systems -- like financial markets -- are populated by thinking, feeling, and socially interacting agents who adapt their behavior and goals as events unfold, causing the underlying relationships that drive system behavior to be both complex (e.g., multiple causes for an effect, positive feedback loops and non-linear relationships between causes and effects, and wide time separation between causes and effects) and unstable over time. This system presents forecasters with a far more difficult challenge. First, because of the system's complexity, there is an irreducible level of uncertainty associated with the identification of the variables to include in a forecasting model, and the specification of the relationships between them. Second, once one has developed a forecasting model, accurately estimating the future values of the included variables and relationships presents a further challenge -- because the system constantly evolves, knowledge of historical values may provide a poor guide to what lies ahead, particularly as the forecast time horizon lengthens. Third, it is often the case that forecasting models and their users are themselves part of the process that drives the evolution of a complex adaptive system. For example, a model that accurately forecasts the price of an asset can be discovered by others, whose subsequent use of the model changes the underlying relationships and competes away its ability to generate profitable predictions.
Beyond understanding the nature of the underlying system, there is the equally challenging issue of the nature of the forecasters themselves. To varying degrees, all human beings are affected by factors that reduce the accuracy of the forecasts they make. Perhaps the most important of these are the so-called "anchoring", "confirmation" and "overconfidence" biases. Anchoring refers to our tendency to insufficiently adjust our forecasts when we receive new information. Confirmation refers to the tendency to pay more attention, and give greater weight to information which supports our current forecast, and less to information which contradicts it. Other studies have repeatedly found that many forecasters are overconfident -- when asked to provide a range that includes 80% or 95% of possible outcomes, most people provide answers that are too narrow compared to actual results. Put differently, we tend to underestimate volatility and variance, and how they compound over time. Finally, recent research in neurobiology has found that increased uncertainty triggers feelings of fear, as well as stronger desire to avoid social isolation. Put differently, when uncertainty rises, we have a natural tendency to follow the herd, and accept the conventional wisdom about what lies ahead. While that was undoubtedly advantageous eons ago when our ancestors were trying to survive on the East African savannah, it often works to our disadvantage when we are trying to survive and prosper in financial markets.
These conclusions are generally in line with what we observe in financial markets, where short term tactical trading models are often highly quantitative and based on recent investor behavior, while long term asset class allocation models focus on fundamental valuation and economic considerations. In the middle lie security and sector investment selection models, which usually include a mix of variables related to fundamental valuation and investor behavior.
Second, as studies have repeatedly shown, investors can increase the accuracy of their predictions (and overcome their confirmation bias) by actively seeking out and combining different forecasts (for a good overview of this research, see "Forecast Combination" by Allan Timmermann). While there are many complex techniques for weighting different forecasts, researchers have found that simple averaging often works surprisingly well, provided that the forecasts are based on different underlying methodologies. This is a critical point, as multiple studies have found that professional forecasters have a tendency to herd (see "Experts' Earning Forecasts: Bias, Herding And Gossamer Information" by Guedj and Bouchaud). The key benefit of forecast combination is that it tends to cancel out some of the model specification and parameter estimation errors in the individual methodologies. Studies showing the benefits of forecast combination are closely related to other research which has found that confidence in a prediction increases when forecasts based on different methodologies reach similar conclusions (see, "The Good, the Bad and The Ugly of Predictive Science" by Hemez and Ben-Haim).
The third technique that can improve the quality of an investor's foresight is to always ask these four questions of any forecast he or she makes or receives: What are the critical assumptions upon which it is based? Which of these are the most uncertain? What indicators will tell me they are not turning out as expected? And where should I look for them? The inescapable fact is that our ability to pay attention to information is limited by time and neurobiology, and is further challenged by the deluge of data that technology delivers to us each day. In today's world, taking a passive approach to the allocation of your scarce attention is likely to reduce the quality of your foresight.
In sum, accurately forecasting the behavior of a complex adaptive system like a financial market is an extremely difficult task, particularly as the time horizon grows longer. Yet it is still possible to improve one's foresight, and to improve your ability to avoid the painful losses and regrets that so many investors have recently experienced.
Interesting New Research
In an update of a previous paper ("Do Individual Investors Have Asymmetric Information Based on Work Experience?"), Doskeland and Hvide analyze (using a very detailed data set from Norway) the validity of an assumption that probably underlies a lot of individual investors' belief in the virtues of active management: Does working in an industry give you an edge? Apparently, lots of people believe that it does, as the authors find that "individuals hold an excess weight in stocks that are professionally close -- for example, even after excluding holdings of own-company and previous employer equity, individuals still hold 11%of their portfolio in stocks within their two digit industry code of employment." Unfortunately, the authors conclude their confidence in their apparent edge is misplaced, finding "no evidence that investments in professionally close stocks are associated with a positive abnormal return in either the short or the long term."
Of course, this begs the question of the underlying causes for this result. We can think of three possible explanations: (1) working in an industry mostly exposes you to information that is already in the public domain, and available to other investors who have already acted on it. (2) Working in an industry makes people overconfident about the potential investing advantage conferred by either private information and/or frameworks for understanding public and private information about an industry, leading to overtrading and negative alpha (in fact, the authors of this paper find this result in some specifications of their model). And/or (3), individual investors face obstacles that prevent them from fully capitalizing on the private information or superior industry models to which they have access (e.g., difficulty in taking short or leveraged positions, high trading costs for individual investors, insufficient time to monitory positions and trade on a timely basis, etc.). Whatever the underlying cause (and we suspect that all three are at work), forewarned is forearmed when it comes to being overconfident about your belief that working in an industry automatically gives you an active investing edge.
As we move into the rebalancing of our model portfolios (which was delayed by the onset of the 2007/2008 crisis), and in light of the behavior of different asset classes during that crisis, we have been focused on two key changes from the past. The first, as regular readers know, is moving from a two regime to a three regime model (from "normal" and "bad" to "normal", "high inflation" and "high uncertainty"). The second is a greater emphasis on directly incorporating “tail risk” hedges (such as the recently introduced funds that track equity volatility indexes) into a portfolio. Our thinking in this area has recently received more support from two new research papers. In "Tails, Fears, and Risk Premia", Bollerslev and Todorov conclude that "compensation for rare [extreme] events accounts for a large fraction of the equity and variance risk premia in the S&P 500 index", and that the fear of disaster varies over time. In "Crash Risk in Currency Markets", Farhi, Fraiberger, Gabaix, Ranciere and Verdelhan conclude that "disaster risk premia account for about 25% of carry trade [borrowing in low interest rate currencies and investing the proceeds in high interest rate currencies] excess returns in advanced countries." Both of these papers reinforced our belief in the value of new instruments that make it possible to take a long position in equity market volatility, and in so doing hedge off a portion of a portfolio's downside tail risk.
Another paper that caught our eye and made us think was "Correlations, Risk and Crisis: From Physiology to Finance" by Goban, Smirnova and Tyukina. We know what you're probably thinking at this point -- something between "get a life" and "gee, you must be so much fun to have at a cocktail party." But bear with us on this one. In this paper, the authors analyze "the dynamics of correlations and variance in systems under the load of environmental factors." So far so good. We've seen that over the past two years, right? And nobody is quite sure of where things are headed, right? Well, these authors provide an interesting framework for thinking about the uncertainty we face. Specifically, they find that "a universal effect of systems under a load of similar factors is that in crisis states, even before obvious symptoms appear, correlation increases, and, at the same time, variance (standard deviation or volatility) increases too. After the crisis achieves its bottom, it can develop in two directions: recovering (both correlations and variance decrease) or fatal catastrophe (correlations decrease, but variances do not)." The authors find that this pattern is common across multiple organisms and complex adaptive systems. On balance, we believe that superior foresight comes from a superior mental model for attending to, and making sense of publicly available information, rather than access to private information. This is especially true in the case of asset allocation, as opposed to sector or security selection within an asset class. Papers like this are important because they help us to continually improve our mental models for making sense of the flood of information that confronts us each day.
Another paper in this class, and one which could eventually have a large impact, is "A Satisficing Alternative to Prospect Theory" by Brown, DeGiorgi, and Sim. The authors integrate a number of strands in behavioral decision research, and formalize a theory of choice in the face of uncertainty that makes good intuitive sense to us. Their approach begins with the decision maker specifying an "aspiration level" -- say a set of accumulation or decumulation goals. They then show how positions that have more than a threshold probability of achieving the target are always preferred (satisficing), while preference for positions (e.g., asset allocations) below this threshold vary depending on the probability they can achieve the target. Specifically, for relatively more "secure" positions -- i.e., those that, while below the satisficing threshold, still have a high probability -- greater diversification is preferred to reduce risk. In contrast, when the available positions are less secure (e.g., when there is less money to invest, relative to an accumulation target), greater concentration (more risk) is preferred, since they have a better chance of attaining the goal than a more diversified portfolio. While technical, this paper breaks new ground in terms of setting out a plausible description of the way people make decisions in the real world.
Finally, we'd like to briefly highlight some interesting findings from "Decision Aid Reliance: A Field Study Involving Professional Buy-Side Financial Analysts" by Hunton, Arnold, and Reck. One of our long-standing research interests is how to improve decision making in the face of uncertainty. Researchers from multiple fields have found that the use of "decision aids" can help in this area, because they focus our attention on the most important elements in a situation and how they are related to each other. A pilot's pre-flight checklist is one example of this. So are standard company financial ratio analyses sheets found on many websites today, and so are our structured approaches to asset class valuation and economic analysis. The authors of this paper analyzed the use of similar decision aids by buy-side analysts at a mutual fund company. Some of their findings were consistent with previous research (little of which, however, had directly studied the use of DAs in the field): reliance on decision aids increased with task complexity and user confidence in the decision aid, and use of the decision aids produced better results. Two other findings were more surprising: first, higher task ability was associated with greater use of decision aids. Apparently, experts better appreciate the advantages of "offloading" some cognitive tasks to decision aids, presumably so they can devote their attention to other analysis and/or synthesis tasks not captured by the decision aids. Could it be that analysts with lower levels of expertise believe (falsely) that higher reliance on decision aids could somehow threaten others’ perception of their competence? The study provides no data, but our experience tells us this is a hypothesis worthy of further investigation. The second surprising finding was that as performance-contingent incentives increased, reliance on decision aids declined. While this paper doesn't isolate the performance impact, previous researchers have found that, beyond a certain point, increasing performance based incentives leads to decreasing performance. Perhaps the analysts in this study felt that in order to outperform, they had to take a different view than what the decision aid suggested. Unfortunately, the higher levels of emotional pressure present when performance incentives are high seem to reduce the likelihood that strategy will work. Again, it would be interesting for someone to directly study that issue -- but experience tells us what they are likely to find.
More News on the Big Changes Underway for Financial Advisers
As regular readers know, there are major changes underway in the financial advisory business in the U.K., Australia, India and the U.S., largely focused on tighter distinctions between the roles of product salesperson and a fiduciary providing advice, and the elimination of commission payments to the latter, with preference given to fee-based compensation. For example, consider the following excerpts from the recent submission of Quantum Financial Services to the Australian Parliamentary Inquiry into Financial Products and Services: "We note the current major issues facing the financial services industry, including low current consumer opinion towards financial planners / financial advisors; recurring examples of failures of financial institutions and rampant abuse of consumers; [and] lack of professionalism among many who hold themselves out as financial planners/financial advisors…"
"The relationship between product providers and advisers completely taints the professional financial planning advice process and decreases consumer confidence in the whole industry. From the clients' perspective, typically they trust the advice of the financial planner that the product that they are recommending is the best one for them. They should be able to rely on that advice, free of conflicts of interest that the relationship between the advice and product creates. In our opinion, unfortunately this third relationship is too strong as product providers actively seek to influence financial planners to direct their clients into their products via the following strategies largely hidden to consumers:
In the U.K., the Financial Services Authority has issued a new consultation paper on its Retail Distribution Review that provides detailed recommendations for the implementation of reforms that have already been proposed, including a ban on commission payments to advisers by the end of 2012. The FSA clearly states that one of its key goals is making sure that "recommendations made by advisers are not influenced by product providers.' In India, there are proposals to ban front end commissions, and to fully disclose trailing commissions. And in the U.S., the Obama Administration has proposed a rule change that would hold registered broker dealer representatives to the same fiduciary standard that now governs the behavior of Registered Investment Advisers, including much more extensive disclosure of compensation arrangements with product providers.
Other recent articles highlight why the changes that have been proposed across many countries are both long-overdue and critical. A recent article in Australia's Money Management noted that "nearly half of all Australian high new worth clients lost confidence in their wealth management firms and financial advisers during the downturn, leading to 26 percent of all HNW clients withdrawing their assets or leaving the firm altogether in 2008." Apparently, this trend was strongest among clients who are under 45 years old. In the U.K., FT Adviser reported the results of a survey that found "forty percent of private investors said they disagreed with the advice they were given by their advisers over the past 24 months, or felt their advisors were too slow to respond to the challenge of the financial crisis." Finally, in the Journal of Indexes, Jack Bogle offered a new analysis that used funds flow data to compare the actual rates of return earned by investors in different ETFs and index mutual funds with the returns on the underlying indexes over the past five years. The clear conclusion was that over-trading (and the relative underperformance it causes) was much worse among ETF investors. As a result, their realized returns underperformed the indexes by much greater amounts than was the case for investors in index mutual funds, who traded much less. In sum, the financial advice industry seems to be at a turning point, not only in those countries where change is already underway, but also elsewhere, in places like the Eurozone and Canada, where the practices criticized in Australia, the U.K., India and the U.S. are also widespread. We cannot help but think that it will be increasingly difficult for the Eurozone and Canada to maintain their current systems after substantial changes have been made in these other countries.
Product News that Caught our Eye
In Canada, iShares has launched two new ETFs, one covering emerging markets (XEM) and one tracking the MSCI World Index (XWD). Encouragingly, these new ETFs carry quite low expenses (.45% and .82%, respectively), which hopefully will add to the downward pressure on the average expenses on Canadian investment products, which are among the highest in the regions we cover. In the U.S., there was yet another criticism of leveraged ETF products, this time from the U.S. Financial Industry Regulatory Authority, in a notice to brokers and registered investment advisers, that is worth quoting at some length: "Most leveraged and inverse ETFs "reset" daily, meaning that they are designed to achieve their stated objectives on a daily basis. Due to the effect of compounding, their performance over longer periods of time can differ significantly from the performance (or inverse of the performance) of their underlying index or benchmark during the same period of time. For example, between December 1, 2008, and April 30, 2009:
This effect can be magnified in volatile markets. Using a two-day example, if the index goes from100 to close at 101 on the first day and back down to close at 100 on the next day, the two-day return of an inverse ETF will be different than if the index had moved up to close at 110 the first day but then back down to close at 100 on the next day. In the first case with low volatility, the inverse ETF loses 0.02 percent; but in the more volatile scenario the inverse ETF loses 1.82 percent. The effects of mathematical compounding can grow significantly over time, leading to scenarios such as those noted above…NASD Rule 2310 requires that, before recommending the purchase, sale or exchange of a security, a firm must have a reasonable basis for believing that the transaction is suitable for the customer to whom the recommendation is made. This analysis has two components. The first is determining whether the product is suitable for any customer, an analysis that requires firms and associated persons to fully understand the products and transactions they recommend. With respect to leveraged and inverse ETFs, this means that a firm must understand the terms and features of the funds, including how they are designed to perform, how they achieve that objective, and the impact that market volatility, the ETF's use of leverage, and the customer's intended holding period will have on their performance. Once a determination is made that a product is generally suitable for at least some investors, a firm must also determine that the product is suitable for the specific customers to whom it is recommended. This analysis includes making reasonable efforts to obtain information concerning the customer's financial status, tax status, investment objectives and such other information used or considered to be reasonable by such member or registered representative in making recommendations to the customer. While the customer-specific suitability analysis depends on the investor’s particular circumstances, inverse and leveraged ETFs typically are not suitable for retail investors who plan to hold them for more than one trading session, particularly in volatile markets."
In the United States, new Macroshares that track the appreciation (UMM) and depreciation (DMM) of prices in major housing markets began trading. It will be interesting to see how much interest there is in them. UMM is attractive to investors without a current exposure to U.S. residential property, who would like to add that asset class to their portfolio (of course, that begs the question of when to buy it -- i.e., when the bottom will be reached -- and how much upside there really is in this asset class, given demographic, credit, and economic trends -- but those are questions for another day). Theoretically, DMM could be used by an existing homeowner to hedge downside exposure; as a practical matter, however, the amounts of money involved may make this strategy too expensive for most. An option on DMM or housing futures might be a less costly approach; hopefully this will develop in the future, and be packaged into products that are accessible to retail investors (or even bundled into new mortgage products). Elsewhere, a new paper by Fabozzi, Shiller and Tunaru ("Hedging Real Estate Risk") provides a very good technical overview of the current state of play in this area.
Last but not least, we note the excellent recent OpEd on longevity bonds in the 28 June 2009 Financial Times by Blake, Boardman, Cairns and Dowd of the Pensions Institute at Cass Business School. They review the arguments in favor of the U.K. government (and indeed, governments elsewhere) funding part of their fiscal deficits with longevity bonds, whose payments would rise with the proportion of the population living to 90 years of age or more. As we have noted in the past, this is a product that is long overdue, which would open up a valuable new asset class to investors.
| Asset Class Valuation Update | This Month's Letters to the Editor: LSC or GCC; VXX and VXZ ETFs; Regency Bias - Balance With New Information | Global Asset Class Returns | Uncorrelated Alpha Strategies Detail | The Outlook for Venture Capital Returns | Product and Strategy Notes: Developing Better Foresight; Interesting New Research; Big Changes Underway for Financial Advisors; and New Products - Canada (XEM and XWD): US Leveraged and Inverse ETF Performance, UMM and DMM and UK Longevity Bonds | July 2009 Issue: Key Points | July 2009 Economic and H1N1 Influenza Update |