Author Archive for Robert Seawright

My Top Ten Non-Investing Books for Investors

By Robert Seawright, Above the Market

Last week, other bloggers and I provided favorite reads for Tadas Viskanta and his terrific site, Abnormal Returns. There are a lot of good and helpful suggestions offered there. But I am seldom asked about books in a broader context — books that changed my overall thinking and thus necessarily changed how I view investing and the markets. The ten books shown in the gallery below did just that. They were (and are) particularly illuminating. I highly recommend them.

Active Management Required

By Robert Seawright, Above the Market

We have all heard the arguments about the flaws of active management and we all should have looked closely at the underlying data. Over any random 12-month period, about 60 percent of mutual fund managers underperform. Lengthen the time period examined to 10 years and the proportion of managers who underperform rises to about 70 percent. Even worse, equity managers who underperform do so by roughly twice as much as the outperforming funds beat their chosen benchmarks and the success of the outperformers doesn’t tend to persist. The SPIVA Scorecard from S&P demonstrates this phenomenon regularly and routinely.

Institutional investors fare no better. On a risk-adjusted basis, 24 percent of funds fall significantly short of their chosen market benchmarks and have negative alpha, 75 percent of funds roughly match the market and have zero alpha, and well under 1 percent achieve superior results after costs—a number not significantly different from zero in a statistical sense. Pension fundshedge fundsendowments and private equity funds all provide similar outcomes in slightly different settings.

Meanwhile, and not surprisingly, assets are following performance. Just a decade or so ago, passive investing was a relatively small slice of the investment universe. On November 1, 2003, just 12 percent of all U.S. open-end mutual fund and ETF assets (not including fund-of-fund or money-market assets) were invested in passively managed products, according to Morningstar. Today that percentage stands at 27 percent and is growing fast. In the equity markets, fully 35 percent of all investments are now held in passive vehicles.

The obvious conclusion from all this data is that active management has lost. Sure, most money is still placed with active managers (at least for now), the story goes, but active management is like Nazi Germany after D-Day. The war wasn’t won (yet) and a lot of work remained to be done, but the outcome was inevitable. That narrative is prevalent throughout the investment world.

However, and to the contrary, I think active management is an absolute necessity.

As an obvious starting point, investing successfully – investing at all – requires the active management of one’s life. The decisions to save, how much to save and how consistently to save must all be actively taken. Figuring out one’s hopes, dreams and goals, developing a plan around them and implementing that plan is decidedly active management. Evaluating risks and opportunities and acting on them is, by definition, an active endeavor. Determining a course, adjusting course as one’s situation changes and staying the course all require action. Staying smart when the markets are going nuts takes active involvement and management, at least with respect to one’s emotions and biases. For all of these crucial matters, passivity and inertia are the enemy. Active management is an absolute necessity.

But I recognize that this argument is more than a bit disingenuous. It isn’t using “active management” in a consistent way or in the way it is most commonly used in our industry. Fair enough. So let’s dig a bit deeper.

As the vast majority of readers will already know, a passive investor most typically looks to hold every security in the market, with the most prevalent of such approaches looking to have each security represented in the same manner and to the same extent as in the market, in order to achieve market returns, usually via index funds. It is a buy-and-hold approach to money management. It guarantees a heavy concentration in the largest, most overly hyped and inflated stocks while requiring that one buy high and sell low but, as John Bogle concedes, “that’s the market.” Even so, indexing beats that vast universe of underperforming active managers.

On the other hand, an active investor is one who is not passive and thus seeks to “beat the market” either in an absolute sense or on a “risk-adjusted” basis. It is often the art of stock picking and market timing, but not always and less-and-less so as time goes on. Because active managers have typically acted on perceptions of mispricing and because these misperceptions change relatively frequently, such managers tend to trade more often – hence the use of the term “active.”

The overall portfolio of a truly passive investor — one who strives to “own” the world market on a cap-weighted basis — will look something like that illustrated below (fromhere).


But of course making the decision to use such a portfolio and to allocate sector weightings by market capitalization require an active decision. Adjusting this portfolio for risk management or for other purposes or other reasons requires active management. For example, deciding to add real estate more accurately to reflect the extent of real estate ownership worldwide or reducing real estate exposure because of home ownership requires active management.

The equity portion of the portfolio will be allocated something like the table (from Greenwich Associates) at right (more here). Bonds will be allocated along these lines. But almost nobody does so (how many American investment portfolios have just a 10-12 percent allocation to domestic equity, for example?). As Jason Zweig reminded me this week, Northern Trust used to have a fund built in this way but it folded world-market-cap-by-countryseveral years ago. Many years ago Brinson sold an open-end fund of this sort through UBS, and Vanguard had something similar for a few years too. But these ventures have all been discontinued due to a lack of investor interest.

However, the more that investors seem to want passive management, the more the fund industry has reacted to that change (sometimes, but not necessarily, for the better). For example, increasing attention has been paid to alternative indexing approaches — so-called “smart beta” – that are built around specific factors (stock price/earnings ratios, company performance, share-price volatility, to name a few). Equal-weighted index investing is also increasingly popular. Choosing any of them is activism, obviously, even if the investment vehicles are quasi-passive (i.e., rules-based, yet the applicable rules must be selected actively).

Similarly, the sorts of approaches that have been shown to work persistently (such as value, size, momentum and profitability) require activism if they are to be utilized. DFA and its very good “asset class diversification” funds and strategies are probably the most prominent examples in this regard. These approaches work but aren’t market portfolios of any sort, even if and when the selection mechanisms are rules-based and/or the underlying vehicles are index funds. It’s active management of a different sort.

Unfortunately, most actively managed funds are actually highly diversified and thus cannot be expected to outperform. The more stocks a portfolio holds, the more closely it resembles an index. The average number of stocks held in actively managed funds is up roughly 100 percent since 1980, according to data from the Center for Research in Security PricesSee Pollet & Wilson, “How Does Size Affect Mutual Fund Behavior?”Journal of Finance, Vol. LXIII, No. 6, p. 2948 (December 2008). Large numbers of positions coupled with average turnover well in excess of 100 percent (per William Harding of Morningstar) effectively undermines the idea that such funds could be anything but a “closest index.”

Numerous studies show that funds which are truly actively managed and more concentrated outperform indices and do so with persistence. See, e.g., Kacperczyk, Sialm & Zheng, “Unobserved Actions of Mutual Funds” (2005); Cohen, Polk & Silli, “Best Ideas” (2010); Wermers, “Is Money Really ‘Smart’? New Evidence on the Relation Between Mutual Fund Flows, Manager Behavior, and Performance Persistence” (2003); Brands, Brown & Gallagher, “Portfolio Concentration and Investment Manager Performance” (2005); and Cremers & Petajisto, “How Active Is Your Fund Manager? A New Measure That Predicts Performance,” (2007).  As summarized by Cremers and Petajisto:

“Funds with the highest Active Share [most active management] outperform their benchmarks both before and after expenses, while funds with the lowest Active Share underperform after expenses …. The best performers are concentrated stock pickers ….We also find strong evidence for performance persistence for the funds with the highest Active Share, even after controlling for momentum. From an investor’s point of view, funds with the highest Active Share, smallest assets, and best one-year performance seem very attractive, outperforming their benchmarks by 6.5% per year net of fees and expenses.”

Accordingly, it is possible to earn higher rates of return with less risk (particularly since risk and volatility are decidedly different things) via the judicious use of active management as traditionally defined. As the saying goes, nobody is managing the risk of an index. By combining a group of securities carefully selected for their limited downside (think “margin of safety”) and high potential return (think “low valuation” or, better yet, “cheap”), the skilled active manager has a real opportunity to stand out (think of investors such as Klarman, Buffett and Abrams). This approach has practical benefits too in that the resources devoted to the analysis (original and ongoing) of each specific investment varies inversely with the number of investments in the portfolio. And it isn’t so different from the factor-tilts used by DFA and others.

The passive revolution doesn’t mean the end of active management, merely an adjustment in its focus. It makes certain well-supported demands, surely, such as lower costs, better diversification, a more careful consideration of rules-based mechanisms and an approach that is comprehensively data-driven at every level. But active management’s death has been erroneously forecast and proclaimed. Good active management is an absolute necessity. Indeed, the greatest need in the financial planning and investment management universes today is good active management.

A Commitment to Truth

By Robert Seawright, Above the Market

It seems to me, after a good deal of thought, reflection and research, that we have so much difficulty dealing with behavioral and cognitive bias in large measure because we build our belief structures precisely backwards. There’s nothing revelatory in that conclusion, obviously, because it is exactly what confirmation bias is all about. We like to think that we make (at least relatively) objective decisions based upon the best available evidence. But the truth is that we are ideological through-and-through and thus tend to make our “decisions” first — based upon our pre-conceived notions — and then backfill to add some supportive reasoning (which need not be very good to be seen as convincing).

I have been working on an infographic to try to illustrate the issue* and have come up with the following.



The goal should be to build from the ground up — beginning with facts, working to conclusions and so on. Beliefs are interpretations of one’s conclusions about the facts. If more fervently held, they rise to the level of conviction and perhaps to the highest pyramid level, whereby one makes a major commitment to a particular cause, approach or ideology. These commitments are the things by which we tend to be defined.

In the real world, we hold our facts relatively loosely and tighten up as we move higher on the pyramid. We all like to be right, but we find it easier to be found wrong on the facts than to be wrong about things in which we have important personal and emotion investments. In a better world, we’d hold onto the facts tightly, as they provide the foundation upon which the rest should be built and they offer our best chance at objectivity. Like scientists, we’d be prepared to alter our thinking with each new fact. However, since facts without interpretation are useless, values need to be mixed in to build an interpretive framework and to make interpretive choices. That said, our values aren’t always factually based or even consciously chosen. They can readily cause us to misperceive the facts.

Conversely, we should hold our beliefs more lightly and try to keep them always subject to the facts and our values. Unfortunately, we readily confuse adjusting our beliefs and convictions in light of new or better evidence with being wishy-washy. For example, we hate it when political candidates flip-flop. We want strong leaders with the convictions and commitments to stand up for truth. Thus much of what counts as political discourse during election campaigns is simply each candidate trying to cast the other as a flip-flopper.

We shouldn’t want leaders who readily relinquish their values in light of difficulty or opposition. We should aspire to that strength ourselves. But we absolutely should want leaders with the humility and insight to make changes when facts and circumstances dictate. We should aspire to that too.

Life experience also conspires to make it more difficult to adjust or amend our positions as we move up the pyramid. The older we get, the more authority we acquire, the more success we achieve, the more prominent we become, the more admired we are, and the more popularity we are bestowed, the harder it is for us to see our mistakes and act accordingly. And since greater conviction leads to greater perceived confidence, certainty and thus credibility and success, it’s easy to continue to fool ourselves, especially when and as things are going well.

There’s a famous expression to the effect that it’s hard to reason someone out of a position that wasn’t reasoned into, and there’s truth in it. It’s hard enough to influence or help alter a person’s beliefs — about religion, politics or even the Yankees’ relative evilness — much less someone’s life commitments (which can be made with respect to religion, politics or almost anything else). But if we’re to have a chance to make better, more reality-based decisions (about investing and everything else), we’re going to have to try and to begin with ourselves.

Given what we know, it should probably start as a commitment, but not a commitment to any cause. Instead, let’s make a commitment to truth, wherever it leads. I’m in, despite my many flaws and errors. I want my commitment to truth — wherever it leads – to be one of my defining features. I hope you’re in too.


* I want to be careful to note that this is a working hypothesis only. I can’t establish it from the data, even though I think it is entirely consistent with the available information (note, for example, research into motivated reasoning, the Semmelweis reflex and the backfire effect). It is also consistent with my experience. Please let me know if and how you look at things differently and the basis for why you do.

The USA — Once an Emerging Market

By Robert Seawright, Above the Market

Scott Krisiloff of Avondale Asset Management has a fine new piece up making the case that we might want to consider lowering our domestic equity return expectations in part on account of ongoing lower dividend yields. That concept is consistent with the long-term trend line for domestic equities. For example, the average return for the S&P 500 indexwas 11.50 percent for the period 1928-2013. For 1964-2013 (the last 50 years), the S&P’s average return dipped to 11.29 percent and from 2004-2013 (the last ten years), the average dropped to 9.10 percent.

It’s surely possible that these declines are more a function of the (arbitrary) dates chosen and/or the vagaries of business and economic cycles rather than a signal of some significant structural change. But it’s also possible that such declines are to be expected given the remarkable changes in the U.S. economy over those decades. It can be easy to forget that the USA hasn’t always been the world’s economic leader, and needn’t remain so (see below).


In the same way that we expect higher returns from investments in emerging and developing economies as compared to those in developed economies on account of higher risks, we might expect aggregate returns in domestic equities to have declined as the American economy has matured. After all, it wasn’t all that long ago that the USA was among the “emerging-est” of emerging markets countries.


The Ubiquity of “Lost Decades”

By Robert Seawright, Above the Market

The financial crisis (circa 2008-2009) brought out discussions about “lost decades” in the investment markets, 10-year periods that suffered negative equity returns. It even prodded PIMCO to argue that the investment universe had fundamentally changed, that an “old normal” had been overtaken by a “new normal” characterized by persistently slow economic growth, high unemployment, significant geopolitical tension with social inequality and strife, high government debt and, of course, lower expected returns in the equity markets.

A Journal of Financial Perspectives paper from last summer considers how unusual it really is for equity markets actually to “lose a decade.” As it turns out, lost decades of this sort are not the exceptional episodes that only very rarely interrupt normal steady economic growth and progress that so many seem to think.

In the paper, Brandeis economist Blake LeBaron finds that the likelihood of a lost decade — as assessed by the historical data for U.S. markets via a diversified portfolio — is actually around 7 percent (in other words, about 1 in 14). Adjusting for inflation (using real rather than nominal return data) makes the probability significantly higher (more like 12 percent, nearly 1 in 8). The chart below (from the paper) shows the calculated return (nominal in yellow, real in dashed) for ten-year periods over the past 200+ years, and shows six periods in which the real return dips into negative numbers.



So a “lost decade” actually happens fairly frequently. As LeBaron summarizes:

The simple message here is that stock markets are volatile. Even in the long-run volatility is still important. These results emphasize that 10-year periods where an equity portfolio loses value in either real or nominal terms should be an event on which investors put some weight when making their investment decisions.

The key practical take-away is that those within 5-10 years of retirement (in either direction) who are taking or planning to take retirement income from an investment portfolio should consider hedging their portfolios so as to avoid sequence risk. Losses close to retirement have a dramatically disproportionate impact on retirement income portfolios. As so often happens, the risks are greater than we tend to appreciate.

5 Good Questions with Terry Odean

By Robert Seawright, Above the Market

Terrance Odean is the Rudd Family Foundation Professor of Finance at the Haas School of Business at the University of California, Berkeley. He is a member of the Journal of Investment Consulting editorial advisory board, of the Russell Sage Behavioral Economics Roundtable, and of the WU Gutmann Center Academic Advisory Board at the Vienna University of Economics and Business. He has been an editor and an associate editor of the Review of Financial Studies, an associate editor of the Journal of Finance, a co-editor of a special issue of Management Science, an associate editor at the Journal of Behavioral Finance, a director of UC Berkeley’s Experimental Social Science Laboratory, a visiting professor at the University of Stavanger, Norway, and the Willis H. Booth Professor of Finance and Banking and Chair of the Finance Group at the Haas School of Business. As an undergraduate at Berkeley, Odean studied Judgment and Decision Making with the 2002 Nobel Laureate in Economics, Daniel Kahneman. This led to his current research focus on how psychologically motivated decisions affect investor welfare and securities prices.

Today I ask (in bold) and Terry answers what I hope are Five Good Questions as part of my longstanding series by that name (see links below).

  1. How much can we really expect to do to overcome our behavioral and cognitive biases?

Someone once said to me, “We can’t control our initial reactions, but we can learn to control what we do next.” Investors will always have cognitive biases. One approach to overcoming them is to practice recognizing biases when they manifest themselves and then adjusting our behavior. This is what Daniel Kahneman describes in Thinking: Fast and Slow as System 2 monitoring System 1. Another approach to overcoming biases is to develop practices and systems that mitigate these biases. For example, if an investor — individual or professional — tends to cling to losing investments, he or she can adopt a rule of automatically selling losers after a predetermined loss. Would this be a perfect solution? Certainly not, but it could be a considerable improvement on current behavior.

  1. Are professional money managers better at dealing with bias than everyone else?

Professional money managers have more opportunity to learn to control their investment biases than do individuals. Some learn. Some don’t. One obstacle is that professional money managers often don’t take a careful look at their own behavior. I’ve been consulting for a company in Boston, Cabot Research, that has developed tools to help professional money managers systematically analyze their past trading decisions to identify biases that are hurting performance.

  1. What are the main differences between individual investors and professional money managers?

Professional money managers devote their working lives to investing. Most individuals invest in their spare time. Professionals work in teams, build institutional knowledge, and make extensive use of computers. Individuals tend to trade on their own. They may have access to public databases, but usually lack the training to do basic analyses such as discounted cash flow valuations of companies. It is difficult for professional money managers to consistently outperform the market by enough to justify their fees. It is even more difficult for individuals to outperform through skill (as opposed to luck) by enough to justify active trading.

  1. What are the most common errors among individuals?

Underdiversification, holding onto losers, chasing winners, buying stocks that catch their attention, systematically ignoring important information, paying too little attention to fees, trading too much.

  1. What are the most common errors among professionals?

I have spent much of my academic career studying individual investors. I’ve had less opportunity to study institutional investors. One difficulty in understanding the biases of institutional investors is that apparent errors could result from biases or they could be driven by how a manager is compensated. For example, managers who have been very successful during the first part of the year often reduce the risk in their portfolio as the year winds down, while managers who have done poorly in the first part of the year tend to increase risk near the end of the year. Why? Managers who have met certain performance targets earlier in the year can often lock in pay incentives by reducing risk at the end of the year; those who are short of the target increase risk in hopes of getting there. Does this behavior make sense for the investors in their funds? No. But it can be understood if you consider the manager’s incentives. On the behavioral side, professional managers may become overconfident, particularly so when they’ve had a good run. Like individuals, many professional managers are reluctant to realize losses. Many professional managers focus most of their attention on the purchases they make and too little on optimizing selling decisions.


Other interviews in the Five Good Questions series:

There’s No Substitute for Good Judgment

By Robert Seawright, Above the Market

“P.T. Barnum was right.”

So says Commander Lyle Tiberius Rourke in the Disney film Atlantis: The Lost Empire, referring to the famous expression attributed to the great American showman: “There’s a sucker born every minute.” Even though Barnum didn’t say it, we get it. In talking about the scientific method in his famous 1974 Cal Techcommencement address, Nobel laureate Richard Feynmanemphasized the point: “The first principle is that you must not fool yourself – and you are the easiest person to fool.”

Accordingly, we’re right to be skeptical about our decision-making abilities in general because our beliefs, judgments and choices are so frequently wrong. That is to say that they are mathematically in error, logically flawed, inconsistent with objective reality, or some combination thereof, largely on account of our behavioral and cognitive biases. Our intuition is simply not to be trusted.

Part of the problem is (as it so often is) explained by Nobel laureate Daniel Kahneman: “A remarkable aspect of your mental life is that you are rarely stumped. … you often have [supposed] answers to questions that you do not completely understand, relying on evidence that you can neither explain nor defend.” We thus jump to conclusions quickly – far too quickly – and without a proper basis.

We aren’t stupid, of course (or at least entirely stupid). Yet even the smartest, most sophisticated and most perceptive among us make such mistakes and make them repeatedly and predictably. That predictability, together with our innate intelligence, offers at least some hope that we can do something meaningful to counteract the problems.

One appropriate response to our difficulties in this area is to create a carefully designed and data-driven investment process with fewer imbedded decisions. When decision-making is risky business, it makes sense to limit the number of decisions that need to be made. For example, it makes sense to use a variety of screens for sorting prospective investments and to make sure that such investments meet certain criteria before we put our money to work.

It’s even tempting to try to create a fully “automated” system. However, the idea that we can (or should) weed-out human judgment entirely is silly. Choices about how to create one’s investment process must be made and somebody (or, better yet, a group of somebodies*) will have to make them. Moreover, a process built to be devoid of human judgment runs grave risks of its own.

Take the case of Adrionna Harris, a sixth grader in Virginia Beach, Virginia, for example.

Last week, Adrionna saw a classmate cutting himself with a razor. She took the razor away, immediately threw it out, and set out to convince him to stop hurting himself. By all accounts, she did what we’d all want our own kids to do. The next day she told school administrators what had happened. The school wouldn’t have known about the incident (and the boy’s situation) if Adrionna hadn’t come forward.

For her troubles, Adrionna didn’t get a parade. She didn’t get congratulated or even get offered thanks. Instead, she received a 10-day suspension with a recommendation for expulsion from school on account of the district’s “zero tolerance” policy. She had handled a dangerous weapon after all, even if just to protect a boy from harming himself. Only after a local television station got involved and started asking pesky questions did common sense prevail – school officials then (finally) agreed to talk with Adrionna’s parents and, in light of the bad publicity, lifted the suspension. When and where discretion is removed entirely, absurd – even dangerous – results can occur despite the best of intentions.

As noted, because our intuition isn’t trustworthy, we need to be sure that our investment process is data-driven at every point. We need to be able to check our work regularly. Generally speaking, it seems to me that the key is to use a carefully developed, consistent process to limit the number of decisions to be made and to avoid making “gut-level” decisions not based upon any evidence but also flexible enough to adjust when and as necessary.

No good process is static. Markets are adaptive and a good investment process needs to be adaptive. Approaches work for a while, sometimes even a long while, and then don’t. Markets change. People change. Trends change. Stuff happens. As Nobel laureate Robert Shiller recently told Institutional Investor magazine, big mistakes come from being “too formulaic and bureaucratic. People who belong to a group that makes decisions have a tendency to self-censor and not express ideas that don’t conform to the perceived professional standard. They’re too professional. They are not creative and imaginative in their approach.” The challenge then is to find a good balance so as to avoid having to make too many decisions while remaining flexible.

Several years ago, the Intelligence Advanced Research Projects Activity, a think tank for the intelligence community, launched the Good Judgment Project, headed by Philip Tetlock, University of Pennsylvania professor and author of the landmark book, Expert Political Judgment, which systematically describes the consistent errors of alleged experts and their lack of accountability for their forecasting failures. The idea is to use forecasting competitions to test the factors that lead analysts to make good decisions and to use what is learned to try to improve decision-making at every level.

The Project uses modern social science methods ranging from harnessing the wisdom of crowds to prediction markets to putting together teams of forecasters. The GJP research team attributes its success to a blend of getting the right people (i.e., the best individual forecasters), offering basic tutorials on inferential traps to avoid and best practices to embrace, concentrating the most talented forecasters onto the same teams, and constantly fine-tuning the aggregation algorithms it uses to combine individual forecasts into a collective prediction on each forecasting question.

Significantly, Tetlock has discovered that experts and so-called experts can be divided roughly into two overlapping yet statistically distinguishable groups. One group fails to make better forecasts than random chance and its decisions are much worse than extrapolation algorithms built with the aggregate forecasts of various groups. However, some of these experts can even beat the extrapolation algorithms sometimes, although not by a wide margin. Interestingly, what distinguishes the good forecasters from the poor ones is a style of thinking.

Poor forecasters tend to see things though one analytical (often ideological) lens. That’s why pundits, who typically see the world through a specific ideological prism, have suchlousy track records. Good forecasters use a wide assortment of analytical tools, seek out information from diverse sources (using “outside” sources is especially important), are comfortable with complexity and uncertainty, and are decidedly less sure of themselves. Sadly, it turns out that experts with the most inflated views of their own forecasting successes tended to attract the most media attention.

“Given the impressive power of this simple technique, we should expect people to go out of their way to use it. But they don’t,” says Harvard psychologist Daniel Gilbert. In a phrase created by Kahneman and his late research partner, Amos Tversky, they often suffer from “theory-induced blindness.” Per Michael Mauboussin, the reason is clear: most of us think of ourselves as different, and better, than those around us. Moreover, we are prone to see our situation as unique and special, or at least different. But in almost all cases, it isn’t.

“My counsel is greater modesty,” Tetlock says. “People should expect less from experts and experts should promise less.” The better forecasters are foxes – who know lots of little things – rather than hedgehogs – who “know” one big thing and who consistently see the world through that lens. For example, reading the first paragraph of a Frank Rich op-ed makes it possible to predict nearly everything the column will contain without having to read another word of it. In systems thinking terms, foxes have many models of the world while hedgehogs have one overarching model of the world. Foxes are skeptical about all grand theories, diffident in their forecasts, and always ready to adjust their ideas based upon what actually happens.

The very best performers are great teams* of people who create careful, data-driven statistical models based upon excellent analysis of the best evidence available in order to establish a rules-driven investment process. Yet, even at this point, the models are not of the be-all/end-all variety. Judgment still matters because all models are approximations at best and only work until they (inevitably) don’t anymore — think Long-Term Capital Management, for example.

Everyone who lives and works in the markets learns to deal with the inevitable – failure, uncertainty, and surprise. Some are better than others. But we can all still improve our decision-making skills and do with proper training.

According to Tetlock, the best way to a become a better forecaster and decision-maker is to get in the habit of making quantitative probability estimates that can be objectively scored for accuracy over long stretches of time. Explicit quantification enables explicit accuracy feedback, which enables learning. We need to be able to check our work quickly and comprehensively. If we can find a basis to justify our poor decisions – if we can find an “out” – we will. Those “outs” need to be prevented before they can be latched onto.

Going through the effort consistently and comprehensively to check our work requires extraordinary organizational patience, but the stakes are high enough to merit such a long-term investment. In the investment world, long-term performance measures provide this sort of accuracy feedback, much to the annoyance of money managers. But it’s hardly enough. Astonishingly, Berkeley’s Terry Odean examined 10,000 individual brokerage accounts to see if stocks bought outperformed stocks sold and found that the reverse was trueSo there is obviously a lot of room for improvement. As in every field, those who make poor decisions propose all sorts of justifications and offer all kinds of excuses. They insist that they were right but early, right but gob-smacked by the highly improbable or unforeseeable, almost right, mostly right or wrong for the right reasons. As always, such nonsense should be interpreted unequivocally as just-plain-wrong.

A quick summary of some of the (often overlapping) ways we can improve our judgment follows.

  • Make sure every decision-maker has positive and negative skin in the game.
  • Focus more on what goes wrong and why than upon what works (what Harvard Medical School’s Atul Gawande calls “the power of negative thinking”).
  • Make sure your investment process is data-driven at every point.
  • Keep the investment process as decentralized as possible.
  • Invoke a proliferation of small-scale experimentation; whenever possible, test the way forward, gingerly, one cautious step at a time.
  • Move and read outside your own circles and interests.
  • Focus on process more than results.
  • Collaborate – especially with people who have very different ideas (what Kahneman calls “adversarial collaboration”).
  • Build in robust accountability mechanisms for yourself and your overall process.
  • Slow down and go through every aspect of the decision again (and again).
  • Establish a talented and empowered team charged with systematically showing you where and how you are wrong. In essence, we all need an empowered devil’s advocate.
  • Before making a big decision, affect a “pre-mortum” in order to legitimize doubt and empower the doubters. Gather a group of people knowledgeable about the decision and provide a brief assignment: “Imagine that we are a year into the future. We implemented the plan as it now exists. The outcome has been a disaster. Take 10 minutes to write a brief history of that disaster.” Discuss.

Per Kahneman, organizations are more likely to succeed at overcoming bias than individuals. That’s partly on account of resources, and partly because self-criticism is so difficult. As described above, perhaps the best check on bad decision-making we have is when someone (or, when possible, an empowered team) we respect sets out to show us where and how we are wrong. Within an organization that means making sure that everyone can be challenged without fear of reprisal and that everyone (and especially anyone in charge) is accountable.

But that doesn’t happen very often. Kahneman routinely asks groups how committed they are to better decision-making and if they are willing to spend even one percent of their budgets on doing so. Sadly, he hasn’t had any takers yet. Smart companies and individuals will take him up on that challenge. Those that are smarter will do even more because there’s no substitute for good judgment.


Teams are much better than individuals (sorry, Bill Gross) and teams of really good forecasters (who, ironically, will almost always be prone to thinking they’ve screwed up) are really, really good (though still often wrong); in GJP tests, they beat the unweighted average (wisdom-of-overall-crowd) by 65 percent; beat the best algorithms of four competitor institutions by 35-60 percent; and beat two prediction markets by 20-35 percent.

We Was Robbed

By Robert Seawright, Above the Market

On June 21, 1932, after Max Schmeling lost his heavyweight boxing title to Jack Sharkey on a controversial split-decision, his managerJoe Jacobs famously intoned, “We was robbed.” It’s a conviction that hits home with every fan of a losing team and thus every sports fan a lot of the time. It’s also a point of view that has received a surprising amount of academic interest and study (note, for example, this famous 1954 paper arising out of a Dartmouth v. Princeton football game).

Traditional economic theory insists that we humans are rational actors making rational decisions amidst uncertainty in order to maximize our marginal utility. As if. We are remarkably crazy a lot of the time.

Behavioral finance examines that craziness by way of the cognitive and behavioral biasesthat impact the investment and economic decisions of individuals and institutions. We like to think that we’re rational actors carefully examining and weighing the available evidence in order to reach the best possible conclusions. Instead, we are much more like spin-doctors, running around looking for anything we might use to support our pre-conceived notions, irrespective of truth.

Confirmation bias is our tendency to notice and accept that which fits within our pre-existing commitments and beliefs. Optimism bias means that our subjective confidence in our judgment is reliably greater than our objective accuracy. And the self-serving biaspushes us to see the world such that the good stuff that happens is our doing while the bad stuff is not our fault. Perhaps worst of all, because of our bias blindness, it isextremely difficult for us to see that there might be something wrong with our own analyses, perspectives and processes.

If you doubt these realities, think about how fans react to wins and losses by their favorite teams. For example, it’s easy to recognize that fans of losing teams will frequently be critical of the officials and that the winners will see the very same calls as appropriate and perhaps necessary. It’s as if the fans of each team watched an entirely different game.

In an effort to provide useful analysis for the maximum number of American sports fans – those whose teams lost over the first week-end of the NCAA Tournament (and I’m one) aren’t likely eagerly to accept the proposition that their criticism of the referees might be a tad misplaced, for example – I will focus on something a bit under the radar in the USA if not elsewhere, a huge soccer (football to the rest of the world) match in Spain Sunday between two perennial powers and perhaps the two best teams in the world today, Barcelona and Real Madrid. Barca won 4-3 to pull within a point of Real and Athletico Madrid at the top of La Liga on the strength of three goals by Lionel Messi and at least as many controversial decisions by referee Alberto Undiano Mallenco. Most neutrals (see here and here, for example), including the Spanish press centered in Madrid, saw the referee as fair if perhaps imperfect.

Not surprisingly, Real partisans saw things differently. Star Cristiano Ronaldo, after the match: “It obviously bugs certain people if Madrid are successful and winning. …I’ve been here for a long time and it seems to generate a lot of envy if we are doing well. People wanted Barcelona back in the title race and now they have that. We aren’t treated equally.” Moreover, “Real Madrid is the biggest club and that creates a lot of envy around it. You can say that the treatment is the same, but it’s not.” He also told his club’s official website: “We are sad because we knew we deserved more, but the fight goes on.”

Sergio Ramos, who was given a red card ejection in the second half, ominously told reporters that “somebody” had wanted Madrid to lose. “It is clear that when you are the best team in the world there is envy in some places. We at Real Madrid suffer from that and must fight against it. Even though there are some things against which you cannot fight.” Real coach Carlo Ancelotti was more tactful but no less clear: “We played well. We did not deserve to lose.” Moreover, “[w]e have to be happy with the way we played this game, luck was not on our side….” Predictably, the protests went nowhere.

Notice the losers’ refrain. They did what they could but bad luck controlled the outcome. They saw what they wanted to see. And so did the referee community, as Spain’s referees committee (El Comité de Árbitros) “denounced” the conspiracy theories, filed an official complaint with league officials and – in an odd move – called to congratulate the game referee on a job well done.

Predictably, Barca thought the officiating was just fine. Star midfielder Xavi Hernandez: “…I believe the referee was fair. They told me later that the penalty [that Ronaldo won] by Alves is outside, and we practically did not even protest. I would have whistled what [the referee] whistled, that’s the truth. I saw clear penalties. We need to focus on the analysis that Barcelona were superior to Madrid, played better and the result is there.”

Notice the winners’ contrasting theme. They deserved to win and the result followed. They too saw what they wanted to see.

Meanwhile, Athletico Madrid president Enrique Cerezo, whose club is now tied with Real and just ahead of Barca, could afford to try to put himself above the fray. “To complain when something is immovable is not worth the effort,” Cerezo said. “You cannot change anything at that point. I saw the Madrid-Barcelona game and if in one of the penalties whistled, even after seeing the replays, we did not know exactly what happened, how can you ask something different of the referee? They get things right the majority of times.” Somehow I doubt that his response would have been so magnanimous if his club had been playing and some tough calls had gone against them.

Everybody else may be biased, but we remain convinced that we routinely come to careful and objective conclusions for ourselves, even about the officiating in a game we care passionately about. We’re certain of our own abilities and objectivity. We aren’t flawed. We was robbed. In short (and as I routinely note), we remain convinced that we routinely see things as they really are. The sad truth is that we do nothing of the sort. Instead, we see things the way we really are.

A Reason to Worry

By Robert Seawright, Above the Market

Last week we passed the five-year anniversary of the post-financial crisis lows. The ongoing bull market, fueled by decent economic news and an activist Fed, may well continue for a long time yet. I don’t have a crystal ball.

But I saw a reason to worry this morning: this article at Benzinga (also highlighted at MSN Money and Yahoo! Finance). Yup. We’re back to seeing arguments that people should take out home equity loans in order to buy stocks – because that tactic has worked out so well in the past!?! It’s as if leverage doesn’t come with major inherent dangers, especially at the retail level.

If an advisor were to pitch such a scheme, the regulators would be all over it. Note, for example, this Investor Alert from FINRA.

We are issuing this alert because we are concerned that investors who must rely on investment returns to make their mortgage payments could end up defaulting on their home loans if their investments decline and they are unable to meet their monthly mortgage payments. In short, investors who bet the ranch could lose it.

As Felix Salmon put it, “it’s pretty much always a bad idea to borrow money and invest it in the stock market — and it’s an even worse idea to borrow money against your house and invest it in the stock market.”

Maybe this article is signalling a market top. Or maybe it’s just silly and dangerous. But it surely shows that we have been in a very good market cycle for a long time now. And that makes me nervous.

Yale Model Heat Check

By Robert Seawright, Above the Market

With a new report out from the Yale Endowment, now is a good time to do a heat check on how the so-called “Yale Model” of investing is doing. I have written about the Yale Model numerous times (see herehere,here and here, for example). It emphasizes broad and deep diversification and seeks to exploit the risk premiums offered by equity-oriented and illiquid investments to investors with an investment horizon that’s sufficiently long – in Yale’s case, essentially forever. It has worked exceptionally well for Yale. For others…not so much.

The newest report from David Swensen and the Yale Endowment was released last weekand demonstrates that the university has been well-served by its Endowment and the investment approach it (and he) pioneered. For fiscal 2013 (ending June 30, 2013), Yale earned a 12.5 percent return, well ahead of the 11.3 percent average for foundations and endowments, if lower than domestic public equities (that should be expected in a year when one investment class dramatically outperforms).

With annual net ten-year investment returns of 11 percent and 20-year returns of 13.5 percent, the Endowment has grown substantially, despite significant institutional expenditures therefrom. Perhaps most significantly, if Yale’s assets had been invested in a classic 60:40 portfolio since 1988, the Endowment’s value today would total $9.11 billion, far less than its current value of $20.78 billion.

For the current year, target allocations to real estate (19 percent) decreased by 3 percentage points and private equity (31 percent) by 4 percentage points, reflecting Yale’s view of the relative opportunities in those sectors. Approximately one-half of the portfolio is illiquid. Roughly 95 percent is allocated to equity and equity-like investments.

I have questioned whether the Yale Model is “past it” – whether its approach is now so often copied that the “trade” is crowded and alpha is dissipated. This year’s report strongly contends that such alpha remains available, but reiterates that it isn’t available to everyone. As the report points out, “Yale has never viewed the mean return for alternative assets as particularly compelling.” The key to success for Yale is access to the best managers, at the best price, with a careful alignment of interests. Since Yale is aligned with the best managers – who are not taking on new investors – the Endowment believes that it is healthy and needn’t alter its strategy.

For investors who came later to the party, the prospects aren’t nearly as good. “While alpha is not dead, opportunities to access it may not be available to all investors.” For example, with respect to private real estate, the report notes that “[t]he illiquid nature of private real estate and the time-consuming process of completing transactions create a high hurdle for casual investors.” Thus “[t]he costly game of active management guarantees failure for the casual participant.”

According to Yale’s own analysis, an “average endowment” runs a 28 percent chance of losing half of its assets (in real terms) over the next 50 years and a 35 percent chance risk of a “spending disruption” over the next five years, on account of asset allocation decisions. That’s far greater risk than most investors (and nearly all individual investors) can bear. The newest report also includes an explicit warning to investors who aren’t Yale.

“Few institutions and even fewer individuals exhibit the ability and commit the resources to produce risk-adjusted excess returns.

“… No middle ground exists. Low-cost passive strategies suit the overwhelming number of individual and institutional investors without the time, resources, and ability to make high-quality active management decisions. The framework of the Yale model applies to only a small number of investors with the resources and temperament to pursue the grail of risk-adjusted excess returns.”

In other words, the first people to the buffet table get most of the tasty stuff. Everybody else would be better off eating elsewhere. Significantly, and by way of example, Cambridge Associates estimates that three percent of venture capital firms — which have provided a huge proportion of Yale’s excess performance — generate 95 percent of the industry’s returns and adds that there is little change in the composition of those three percent of firms over time (more here). Yale has ongoing access to that three percent. Few others do (and if you aren’t sure, you don’t).

Note Swensen’s own words of warning.

“At the active end of the spectrum, you’ve got institutions like Yale and Harvard and Princeton and Stanford and others, who’ve really built high-quality investment teams that have a shot at making consistently good active management decisions. But there’s a vanishingly small number of such investors. Those on the passive end of the spectrum have figured out that they don’t know enough to be active. The passive group is not nearly as big as it should be. Almost everybody should be there.”

The Consensus Portfolio

By Robert Seawright, Above the Market

Every year Barron’s reports on the Penta asset-allocation survey of 40 leading wealth management firms (such as Barclays, Fidelity, Goldman Sachs, JPMorgan, LPL, Morgan Stanley, Northern Trust and the like), which outlines in broad terms what those firms’ base recommended portfolios look like. The new survey is noteworthy in that overall allocations to stocks rose to an average of 51.1 percent, up from 48 percent at this time last year and 45 percent in early 2012; fixed-income holdings continued a two-year decline, now at an average 25.8 percent, down from 29 percent last year and 34 percent in 2012; and recommended hedge fund and private-equity allocations, recently “the expensive disappointments of the portfolio” and subject to widespread criticism, are up to an average of 14.1 percent from 12.5 percent last year, with all alternatives (including real estate and commodities) now weighing in at an average allocation of 20.4 percent. A more detailed breakdown is charted below.


Bringing the Stupid

By Robert Seawright, Above the Market

Earlier this week I wrote about the growth of the sports analytics movement, particularly in baseball, as an inevitable outgrowth of trying to make one’s beliefs data-driven and thus reality-based. “Arguments and beliefs that are not reality-based are bound to fail, and to fail sooner rather than later.” I also noted that the investment world needs similar growth and development.

But despite the exponential growth in the use of analytics (earlier this year the Phillies became the last Major League Baseball team to hire a full-blown stats guy), not everyone in baseball (as with investing) has gotten the message. For example, The Book goes into great detail about the percentages and when it makes sense to execute a sacrifice bunt and finds — conclusively — that sacrifice bunts are grossly overused and rarely make sense. Simply going back over previous games so as (a) to calculate how many runs each team scored when it had a runner on first and nobody out, and (b) to compare those results to when teams had a runner on second and one out, makes the general point pretty well. In fact, Baseball Prospectus has a report that shows that sacrifice bunting reduced a team’s run expectancy for innings that played out that way from .83 runs to .64 runs in 2013. The same is generally true in previous years.

Note too that we’re not talking here about difficult concepts or high-level math. It’s just a simple calculation — more teams scored and scored more with runners on first and nobody out by not-bunting than by bunting. Easy.

But not to Texas Rangers manager Ron Washington. Washington likes to sacrifice bunt. In response to a question about the dubious nature of that strategy based upon the math, Washington took offense.

“I think if they try to do that, they’re going to be telling me how to [bleep] manage,” Washington said. “That’s the way I answer that [bleep] question. They can take the analytics on that and shove it up their [bleep][bleep].”

Wow. He even went third person.

“I do it when I feel it’s necessary, not when the analytics feel it’s necessary, not when you guys feel it’s necessary, and not when somebody else feels it’s necessary. It’s when Ron Washington feels it’s necessary. Bottom line.”

Double wow. No matter one’s chosen ideology, if the data doesn’t support it, the risks of continuing on that path are enormous. It’s not the percentage play (by definition). And it’s not the smart play.

Insisting upon a course of action that is shown to be wrong is, quite simply, a recipe for disaster. A good investment strategy, like good baseball strategy, will be – must be – supported by the data. Reality must rule. When it doesn’t, we’re simply bringing the stupid.