Author Archive for Robert Seawright

Facts (and Minds) are Stubborn Things

By Robert Seawright, Above the Market

When making his defense of some British soldiers during the Boston Massacre trials in December of 1770, John Adams (later the second President of the United States) offered a famous insight. “Facts are stubborn things; and whatever may be our wishes, our inclinations, or the dictates of our passion, they cannot alter the state of facts and evidence.”  Legal Papers of John Adams, 3:269. In a similar vein, Sen. Daniel Patrick Moynihan once said that “[e]veryone is entitled to his own opinion, but not to his own facts.”

I have often warned about our proclivity to and preference for stories to the exclusion of data (for example, here, here and here). Because stories are so powerful, we want the facts to be neatly packaged into a compelling narrative. Take a look at John Boswell‘s delightful send-up of this technique in the TED context below.

We crave “wonder, insight [and] ideas.” Facts?  Not so much. As Evgeny Morozov puts it:

Today TED is an insatiable kingpin of international meme laundering—a place where ideas, regardless of their quality, go to seek celebrity, to live in the form of videos, tweets, and now e-books. In the world of TED—or, to use their argot, in the TED “ecosystem”—books become talks, talks become memes, memes become projects, projects become talks, talks become books—and so it goes ad infinitum in the sizzling Stakhanovite cycle of memetics, until any shade of depth or nuance disappears into the virtual void. Richard Dawkins, the father of memetics, should be very proud. Perhaps he can explain how “ideas worth spreading” become “ideas no footnotes can support.”

Felix Salmon’s excellent discussion of this argument in the context of Jonah Lehrer’s sad case (interestingly put into context here), which decries the use of “remixed facts in service of narrative,” establishes clearly (if unsurprisingly) that the facts are frequently too stubborn to fit neatly into a narrative-driven format — whether TED talk, blog post or bestseller. According to Seth Mnookin and reiterated by Salmon, “Lehrer had “the arrogance to believe that he has the right to rejigger reality to make things a little punchier, or a little neater.” Felix perhaps goes beyond Morozov to argue “that TED-think isn’t merely vapid, it’s downright dangerous in the way that it devalues intellectual rigor at the expense of tricksy emotional and narrative devices.”

To be clear, I am entirely in favor of using narrative to illustrate concepts. I am also in favor of making difficult concepts, and science in particular, more accessible. Moreover, there are many TED-talks I find inspiring, illuminating and useful. However, the issue and the danger is in forcing uncooperative (“stubborn”) facts, what Morozov calls “messy reality,” into a glib narrative in ways that simply don’t fit.

We are so susceptible to this problem (and our overarching bias blindness generally) that we fall prey to it often and don’t recognize it. Indeed, Snopes would not exist without our propensity for not letting facts get in the way of a good story. But even ascertaining the bare facts is far more difficult than we tend to think. As William James put it in The Will to Believe (1897): “Roundabout the accredited and orderly facts of every science there ever floats a sort of dust cloud of exceptional observations, of occurrences minute and irregular and seldom met with, which it always proves more easy to ignore than to attend to.”

We are utterly convinced that our senses are open windows through which we experience the real world as it truly is. But all of what we see, hear, touch, taste and smell is a re-creation by our brains – a useful model (guess) about what things “out there” are really like. To paraphrase neuroscientist Chris Frith, each of us is an invisible actor at the center of his or her world, which is designed to be a “map of signs about future possibilities.” Therefore, “[w]hat you’re experiencing is largely the product of what’s inside your head,” says psychologist Ron Rensink. “It’s informed by what comes in through your eyes, but it’s not directly reflecting it.”

In other words, the brain uses a variety of shortcuts to “sift through [the] superabundance of detail” around us (per V.S. Ramachandran and Susan Blakeslee). “At any given moment in our waking lives, our brains are flooded with a bewildering array of sensory inputs, all of which must be incorporated into a coherent perspective that’s based on what stored memories already tell us is true about ourselves and the world.” Accordingly, our default structure is to invent narratives to live by (initially) and then interpreting our experiences in light of these pre-existing narratives. These stories provide easy-to-remember frames of reference wherein we are typically exceptional, heroic, moral and right. Whenever necessary, we misinterpret “facts” or even invent facts out of whole cloth to fill-in the gaps in our knowledge or to explain what we don’t understand.

Sufferers of Korsakoff’s syndrome provide a marvelous (if unfortunate) example of this phenomenon. These people suffer from the inability to transfer short-term to long-term memory due to a thiamine deficiency, often related to excess alcohol intake. When asked a question, they simply invent wonderful and often entirely plausible answers which change each time the question is asked, because they don’t remember what story they told previously.

Cognitive psychologist Richard Warren from the University of Wisconsin recorded himself reading the sentence, “The bill was passed by both houses of the legislature,” cut a middle part of it out of the recording and replaced it with static. When played for subjects, nearly everyone reported hearing both static and the full sentence. Moreover, they couldn’t report when the static had occurred. The auditory system in the brain filled in the missing piece so that the sentence seemed uninterrupted. You don’t perceive blackness every time you blink, do you?

As reported in New Scientist, “We’ve known since the 1960s that memory isn’t like a video recording — it’s reconstructive,” according to psychologist David Gallo of the University of Chicago. The concept of “autobiographical memory” is not a true and accurate record of your past — it is more like a jumble of the remembrances of others, old yearbook and diary entries, photographs and newspaper clippings. “Your memory is often based on what you’ve seen in a photograph or stories from parents or siblings rather than what you can actually recall,” said Kimberley Wade, a memory researcher at the University of Warwick.

Within days of the atrocities of September 11, 2001, psychologists at the University of Illinois at Chicago asked a sampling of people where they were, what they were doing, how they heard the news and who they were with at that time. A year later they asked them again. More than half of the participants had changed their story on at least one count — while still expressing supreme confidence that their memories were accurate.Other studies confirm these results.

None of us starts our thinking or even our observing with a blank sheet of paper (so to speak). As Quine has shown philosophically (using his metaphor of the “web of belief”) and as vast quantities of research have shown practically, anyone sufficiently motivated to hold onto a conviction can always do so and usually will. All of our fact-finding and analysis is done in connection to our overarching beliefs and viewpoints — the stories we live by and the ways we see the world. Our attitude is often on the order of “Don’t bother me with the facts; I’ve already made up my mind.”

This problem is hardly a new one. More than half a century ago, Stanford psychologist Leon Festinger described the issue pretty clearly in the opening lines of his book, When Prophecy Fails. “A man with a conviction is a hard man to change. Tell him you disagree and he turns away. Show him facts or figures and he questions your sources. Appeal to logic and he fails to see your point.”

To wax philosophical for a moment, there is a longstanding dispute on the nature of truth. Correspondence theory asserts that something is true to the extent that it corresponds to reality (from Aquinas). That’s pretty much the way we usually think about truth to the extent we actually think about it. Unfortunately, even straightforward facts require interpretation to have meaning (as my masthead proclaims, information is cheap; meaning is expensive). Worse, most things in life — including most of the really important things, like morality and justice — cannot be established to any degree of relative certainty. They must be argued for.

In that context, a coherence theory of truth makes sense.* Truth is ascertained by its level of coherence to a set of specified propositions. Thus one who values equality over freedom generally will tend to favor a policy that increases equality even if and when it inhibits freedom. However, the trouble here is that there is no way to come up with a set of foundational propositions without using correspondence and, more fundamentally for practical purposes, no way to adjudicate disputes about truth in this context, even in theory (why should one necessarily favor equality over freedom or vice versa?). In other words, our undergirding propositions (often narratives and beliefs) can be and often are wrong and usually disputed, throwing a monkey wrench into the whole works. Moreover, because reality is so “messy” we ought to be extremely skeptical about very high levels of coherence. I tend to doubt anyone who spins every item of fact into a neat little package supporting his or her point of view.

And therein lies the rub. Our brains are designed to operate using coherence theory without requiring that the underlying propositions be true (even to the extent possible). We start with narrative and belief and spend our time trying to cram the facts (as we see them) into our preconceived notions about the way the world works. Facts may well be stubborn things essentially, but our mental mindset ( a less redundant concept than you might think) means that they are not nearly stubborn enough. That’s because our minds are far more stubborn still.


* The pragmatic theory of truth (from James) holds that true statements are those that work for us and meet our needs better than their alternatives. For these purposes, this approach has the same difficulties as coherence theory.

A much earlier and shorter version of this piece appeared here.


Beguiled by Narrative

By Robert Seawright, Above the Market


The photograph above, taken at the Brooklyn waterfront on the afternoon of September 11, 2001 by German photographer Thomas Hoepker, is now one of the iconic images of that horrible day. In fact, the Observer New Review (London) republished it in 2011 as the 9/11 photograph. In Hoepker’s words, he saw “an almost idyllic scene near a restaurant — flowers, cypress trees, a group of young people sitting in the bright sunshine of this splendid late summer day while the dark, thick plume of smoke was rising in the background.” By his reckoning, even though he had paused but for a moment and didn’t speak to anyone in the picture, Hoepker was concerned that the people in the photo “were not stirred” by the events at the World Trade Center — they “didn’t seem to care.” Hoepker published many images from that day, but he withheld this picture for over four years because, in his view, it “did not reflect at all what had transpired on that day.”

In 2006, the image was finally published in David Friend’s book, Watching the World ChangeFrank Rich wrote a 9.11 fifth anniversary column in The New York Times, framed by the photo, which he called “shocking.” Rich claimed that the five New Yorkers were “relaxing” and were already “mov[ing] on” from the attacks. Rich described those in the photo as being on “what seems to be a lunch or bike-riding break, enjoying the radiant late-summer sun and chatting away as cascades of smoke engulf Lower Manhattan in the background.” Indeed, Rich’s explanatory narrative is hardly complimentary.

Mr. Hoepker’s photo is prescient as well as important — a snapshot of history soon to come. What he caught was this: Traumatic as the attack on America was, 9/11 would recede quickly for many. This is a country that likes to move on, and fast. The young people in Mr. Hoepker’s photo aren’t necessarily callous. They’re just American.

It was a plausible — if utterly speculative — interpretation based upon the photograph alone. More importantly, it framed Rich’s desired narrative perfectly. But even though a picture may well be worth a thousand words (1,506 in this case, to be exact), those words aren’t necessarily all that accurate.

Daniel Plotz quickly came forward with an alternative interpretation that disputed Rich, calling Rich’s reading of the image a “cheap shot.” In Plotz’s view the five had not ignored or moved beyond 9.11 but had “turned toward each other for solace and for debate.” To his credit, Plotz emphasized that he didn’t “really know” what the pictured people were doing and feeling and called upon them to contact him so as to set the record straight. Two did, and they repudiated Rich’s narrative in the strongest of terms.

The first to respond was Walter Sipser, a Brooklyn artist and the man on the far right in the shot. “A snapshot can make mourners attending a funeral look like they’re having a party,” he wrote. “Had Hoepker walked fifty feet over to introduce himself he would have discovered a bunch of New Yorkers in the middle of an animated discussion about what had just happened.”

Chris Schiavo, a professional photographer, Sipser’s then-girlfriend and second from the right above, also responded. She criticized both Rich and Hoepker for their “cynical expression of an assumed reality.” As a “third-generation native New Yorker, who knows and loves every square inch of this city,” whose “mother even worked for Minoru Yamasaki, the World Trade Center architect,” she stated that “it was genetically impossible for [her] to be unaffected by this event.”

So much for the accuracy of Rich’s story.

We love stories, true or not, almost from the cradle. Stories are crucial to how we make sense of reality. They help us to explain, understand and interpret the world around us. They also give us a frame of reference we can use to remember the concepts we take them to represent. Whether measured by my grandchildren begging for one (or “just” one more), the book industry, data visualization, television, journalism (which reports “stories”),the movies, the parables of Jesus, video games, or even country music (“every song tells a story”), story is perhaps the overarching human experience. It’s how we think and respond. We always want to know what happens next.

Stories are culture’s way of teaching us what is important. They are what allow us to imagine what might happen next – and beyond – so as to prepare for it. We are hardwiredto respond to story. A good story doesn’t feel like a story – it feels exactly like real life, but most decidedly is not like real life. It is simplified and otherwise altered. We prefer rhetorical grace and an emotional charge to the work of hard thought. Because we are inveterate simplifiers, we prefer clean and clear narrative to messy reality. A famous book by Karl Popper, The Poverty of Historicism, pretty well demolished the popular notion that history was a narrative, that it had a shape, a progression, and followed laws of development. But we believe that it does (or devoutly wish to believe that it does) anyway.

Still, because it feels so true (“It can’t be wrong when it feels so right”), it isn’t hyperbole to say you’ve been lost in a story. Story turns us into willing students, eager to learn the story’s message. It’s how we sift through the raw data of our lives to ascertain what matters. Our brains are designed to analyze the environment, pick out the important parts, and use those bits to extrapolate linearly and simplistically about and into the future.

Ultimately, the key to a good story isn’t just what happens or to whom it happens. AsRoger Ebert so eloquently put it, broadened ever so slightly, a story “is not about what it’s about; it’s about how it’s about it.” Stories are about how the protagonist changes and how we react to those changes and ourselves change. We can “see” the world as it isn’t.(yet) and as it might become.

The best stories are simple, easily communicated, easily grasped and easily remembered. Perhaps most significantly, we inherently prefer narrative to data — often to the detriment of our understanding. To do math, neither maturity nor knowledge of human nature and experience are required. All that is required is the ability to perceive patterns, logical rules and linkages. But because of the enormous sets of random variables involved in real life, patterns, logical rules and linkages alone do not solve any actual puzzles. Correlation does not imply causation. Information may be cheap but meaning is both expensive and elusive.

As Nassim Taleb explains in The Black Swan, the narrative fallacy addresses our limited ability to look at sequences of facts without weaving an (often erroneous)explanation into them or, equivalently, forcing a logical link, an arrow of relationship upon them. Explanations bind facts together. They make them all the more easily remembered; they help them make more sense. Where this propensity often goes wrong is when it increases our impression of understanding.

Frank Rich — I’m looking at you.

Five years after the towers came down, Frank Rich had a story to tell. It was a story of a “divided and dispirited” America that had lost touch with the horror of 9.11, of a forgetful nation desperate to move on, a divided nation insufficiently stirred. It was also the story of a callow, fear-mongering President with a selfish and secret partisan agenda far removed from committed sacrifice for the common good. It was a story of a once-great country that had moved on but not ahead. And he thought he had found the perfect picture to illustrate that story.

As a journalist, Rich had an obligation to check the facts of his story. By all appearances, he did not. Perhaps he thought it was “too good to check.” If so, he was dreadfully and blatantly wrong. Perhaps he tried and was unsuccessful or that Hoepker’s description was enough to go on. If so, he didn’t try hard enough and also had an obligation to be forthright about what he knew and what was mere speculation. That he did not was an egregious error, an error that would make him look silly when the truth came out, as it so often does.

Many of our foibles (narrative and otherwise) are the result of our laziness. Sometimes the laziness is overt. Other times it is simply a function of the various shortcuts we take, sometimes reasonably, to make life more manageable. Rich took a variety of shortcuts in writing his story, shortcuts that perverted the truth of what the Hoepker photograph actually portrayed. His facts were wrong, plain and simple.

We like to think that we are like judges, that we carefully gather and evaluate facts and data before coming to an objective and well-founded conclusion. Instead, we cut straight to the chase. We are much more like lawyers, grasping for any scrap of purported evidence we can exploit to support our preconceived notions and allegiances. Doing so is a common cognitive shortcut such that “truthiness” — “truth that comes from the gut” per the comedian Stephen Colbert — seems more useful than actual, verifiable fact. Whatreally matters is that which “seems like truth – the truth we want to exist.” That’s because “the facts can change, but my opinion will never change, no matter what the facts are.”

The concept even “became a lexical prize jewel” for Rich himself (see here, for example), allowing him (of course) to criticize his political opponents for offering only “a thick fog of truthiness” such that they presented “a bogus alternative reality so relentless it can overwhelm any haphazard journalistic stabs at puncturing it.” Rich has expounded on the idea a number of times in print and even on The Oprah Winfrey Show. Of course, he always directs the analysis outward rather than inward. Oh the delicious irony.

This concept of “truthiness” captures how, as cognitive psychologist Eryn Newman puts it, “smart, sophisticated people” can go astray on matters of fact. Newman’s research has shown that the less effort it takes to process a factual claim, the more accurate it seems. In one classic study, for example, people were more likely to think a statement was true when it was written in high color contrast as opposed to low contrast. Easy-to-pronounce ticker symbols (such as KAR) perform better in the markets than their difficult-to-pronounce counterparts (such as RDO) — even after just one day of trading. And, astonishingly, claims attributed to people with easy-to-pronounce names were deemed more credible than those attributed to people with difficult-to-pronounce names. Assummarized by Slate recently: “When we fluidly and frictionlessly absorb a piece of information, one that perhaps snaps neatly onto our existing belief structures, we are filled with a sense of comfort, familiarity, and trust. The information strikes us as credible, and we are more likely to affirm it — whether or not we should.”

Due to our affinity for like-minded people, we seek out the people like us to provide echo chambers for our own claims, claims that perpetuate themselves every time we hear them reverberated back to us. We are neuro-chemically confirmation bias addicts. As such, we tend to reach our conclusions first. Only thereafter do we gather purported facts and, even then, see those facts in such a way as to support our pre-conceived conclusions. When it fits with our desired narrative, so much the better. Writing op-eds forThe New York Times provided Rich with a heady and exclusive echo chamber, but an echo chamber nonetheless. Keeping one’s analysis and interpretation of the facts of a story reasonably objective — since analysis and interpretation are required for data to be actionable — is really, really hard in the best of circumstances, even when one has gotten the facts close to right.

Megan McArdle summed things up nicely earlier this week.

We like studies and facts that confirm what we already believe, especially when what we believe is that we are nicer, smarter and more rational than other people. We especially like to hear that when we are engaged in some sort of bruising contest with those wicked troglodytes — say, for political and cultural control of the country we both inhabit. When we are presented with what seems to be evidence for these propositions, we don’t tend to investigate it too closely. The temptation is common to all political persuasions, and it requires a constant mustering of will to resist it.

Frank Rich — I’m looking at you.

Once we have bought-in to a particular narrative, it becomes increasingly more difficult to falsify, even (especially!) when presented with contradicting fact. Take the example of parents who choose not to vaccinate their children and the pediatricians who try to convince them otherwise. When presented with unequivocal information that autism diagnosis and vaccinations were not linked, the strategy backfired and parent became more set in their ignorance. In other words, the disconfirming facts offered actually (in effect) turned up the volume inside the echo chamber such that the truth could not be heard.

The more we repeat and reiterate our explanatory narratives, the harder it is to recognize evidence that ought to cause us to re-evaluate our prior conclusions. By making it a careful habit skeptically to re-think our prior interpretations and conclusions, we at leastgive ourselves a fighting chance to correct the mistakes that we will inevitably make. As with everything in science, each conclusion we draw must be tentative and subject to revision when the facts so demand. As John Maynard Keynes famously stated, “When the facts change, I change my mind. What do you do, sir?” Indeed, what do you do?


Note: This post is a much-expanded version of one that appeared here.

Trouble in Paradise

By Robert Seawright, Above the Market

It’s a problem that is now — finally — discussed and sometimes dealt with. Increasingly, investors of various type are questioning high-cost, high-risk strategies (often purveyed by hedge funds) because they have performed so poorly. Indeed, hedge funds as a class have performedmuch worse even than U.S. Treasury bills. As a consequence, few can expect to achieve success in that market, as I have argued repeatedly (see hereherehere and here, for example). Calpers, the public pension giant here in California, is a leader in this trend that is demanding accountability, putting new investment proposals on hold while weighing whether to exit or substantially reduce bets on commodities, actively managed company stocks and hedge funds.

The general problem is well illustrated right here in San Diego and outlined in a terrificcolumn in the San Diego Union-Tribune yesterday by Dan McSwain. Many cities have a pension crisis. San Diego’s is particularly bad, as outlined definitively by the great Roger Lowenstein in While America Aged. McSwain’s piece does an excellent job of examining how the City is responding to the problem in terms of investment management and contrasting the City’s efforts with what the County of San Diego is doing with its pension dollars. 

To be sure, the City’s pension crisis is much more a matter of political mistakes — mostly by promising too much to City workers — than investment mistakes, as Lowenstein so clearly explains. However, it is still good to see that the City now invests fairly prudently and carefully, with no leverage. And, over roughly the past five years, the City has earned 13.6 percent annually, essentially equivalent to a standard 60:40 portfolio over that same period. That’s very good news.

The County, on the other hand, uses hedge fund-type strategies (almost anything is fair game) newly spiced up by leverage of up to 100 percent and wrapped in an extremely high fee structure (well over $100 million in fees during fiscal 2013). What could go wrong? For a clue to the answer, take a look at another Roger Lowenstein book, When Genius Failed. Not surprisingly, performance to date has lagged badly using this approach. Over the roughly five-year period during which the City earned 13.6 percent, the County paid a lot more and earned a whole lot less — only 9.7 percent — in thriving bull markets for both stocks and bonds. To make the magnitude of the problem a bit clearer, a $10 billion portfolio (that’s about the size of the County’s pension fund today) that earns 13.6 percent over five years grows to over $19 billion. Meanwhile, a $10 billion portfolio that earns 9.7 percent over that same period grows to nearly $16 billion, over $3 billion less. That’s three b-i-l-l-i-o-n dollars.*


As a citizen and taxpayer of both the City and the County, I hope both pension funds succeed spectacularly. Taxpayers will have to fund any shortfalls after all. From an investment standpoint, the City looks to be doing a pretty good job. The County — not so much. Sadly, this isn’t likely to turn out well for the County, and we taxpayers will be left holding the (empty) bag.


* To be clear, I don’t mean to suggest that the County’s opportunity cost was necessarily $3 billion. The County had substantially less than $10 billion in its pension fund five years ago and made contributions to it between then and now.  But the investment scheme the County utilized still came with enormous opportunity costs in terms of returns and risk and the added leverage/risk that has been newly approved makes things even worse. It’s essentially impossible to make a reasonable case justifying it.

Proof Negative

By Robert Seawright, Above the Market


I have regularly argued that in investing, as in most things in life, disconfirmation is more valuable than confirmation (see here, for example). In other words, we learn more from what doesn’t work than from what does. That’s largely because induction is the way science advances.

We want deductive proof, but have to settle for induction. That’s because science never fully proves anything. It analyzes the available data and, when the force of the data is strong enough, it makes tentative conclusions. But these conclusions are always subject to modification or even outright rejection based upon further evidence gathering. The great value of data is not so much that it points toward the correct conclusion (even though it does), but that it allows us the ability to show that some things are conclusively wrong.

In other words, confirming evidence adds to the inductive case but doesn’t prove anything conclusively. Correlation is not causation and all that. Thus disconfirming evidence is immensely (and far more) valuable. It allows us conclusively to eliminate some ideas, approaches or hypotheses.

That said, we don’t like disconfirming evidence and we tend to neglect the limits of induction. Few papers get published establishing that something doesn’t work. Instead, we tend to spend the bulk of our time looking (and data-mining) for an approach that seems to work or even for evidence we can use to support our preconceived notions.

We should be spending much more of our time focused upon a search for disconfirming evidence for what we think (there are excellent behavioral reasons for doing so too). But we don’t, as illustrated by the following question (a variation of the Wason selection task).


Most people answer with E and 4, but that’s wrong. For the posited statement to be true, the E card must have an even number on the other side of it and the 7 card must have a consonant on the other side. It doesn’t matter what’s on the other side of the 4 card. But we turn the 4 card over because we intuitively want confirming evidence. And we don’t think to turn over the 7 card because we tend not to look for disconfirming evidence, even when it would be “proof negative” that the given hypothesis is incorrect. In a variety of test environments, fewer than 10 percent of people get the right answer to this type of question.

I suspect that this cognitive failing is a natural result of our constant search for meaning in an environment where noise is everywhere and signal vanishingly difficult to detect. Randomness is difficult for us to deal with. We are meaning-makers at every level and in nearly every situation. Yet, as I have noted often and as my masthead proclaims,information is cheap while meaning is expensive and elusive. Therefore, we tend to short-circuit good process to get to the end result – typically and not so coincidentally the result we wanted all along.

As noted above, science progresses not via verification (which can only be inferred) but by falsification (which, if established and itself verified, provides relative certainty only as to what is not true). Thank you, Karl Popper. In the investment world, as in science generally, we need to build our investment processes from the ground up, with hypotheses offered only after a careful analysis of all relevant facts and tentatively held only to the extent the facts and data allow. Accordingly, we need always to be on the look-out for disconfirming evidence — proof negative — even though doing so is oh so counterintuitive pretty much all the time.

Above the Market’s Leading Investment Indicators

By Robert Seawright, Above the Market

This fifth edition of Above the Market’s Leading Investment Indicators is for mid-year 2014 and the first since last July. Earlier iterations are hereherehere andhere. As I always note, in economics, leading indicators are measures that typically change before the economy as a whole changes, thus providing some predictive power with respect to what lies ahead. For example, the Conference Board publishes a Leading Economic Index intended to forecast future economic activity.

My intent has been and still is to derive some Leading Investment Indicators. Unlike leading economic indicators, these were not designed as short-term or even intermediate-term predictors. The strength of these metrics is as a tool to measure potential real long-term returns. Thus they are better used as longer term indicators of value, risk and expected returns. They in no way should be used as any sort of timing mechanism. The stock market can continue higher or lower regardless of what any metric of valuation is showing. These indicators are designed to be a tool to help shape an overall investment thesis and process as well as to separate short-term and long-term concerns, not to dictate trading decisions.

My previous conclusions suggested that the market was not long-term cheap. I think they are worth re-visiting in light of recent events (or lack thereof) and as we pass the mid-point of 2014. But I won’t bury the lead (or even the lede). Stocks remain rich and the secular bear market continues (despite the long cyclical bull market rally, fueled by the Fed). Fed activity, as intended, makes stocks look much more attractive than they otherwise would — sort of like being the skinniest kid at fat camp.

As I have noted repeatedly, trying to fight the Fed hasn’t been a very productive approach over the recent past. If you’re going to play (and the risks of sitting things out are big too), please be careful and consider putting on a hedging strategy of some sort. So here goes….

1. PE10. The largest overall contributing factor to equity returns is the P/E ratio. The expansion or contraction of the broad market P/E ratio creates secular bull and bear markets. The chart below from Crestmont Research breaks down the components of total return for the S&P 500 for ten-year rolling periods. As of this writing, P/E is 19.71, well above the mean of 15.51, the median of 14.56 and last year’s level of 18.18..


Yale Professor Robert Shiller’s 10-year Average Inflation-Adjusted PE Ratio, also known as CAPE, Shiller PE or PE10, provides the best longer-term market gauge available. PE10 is the stock index price divided by the average real earnings from the previous 10 years – the time period is designed to smooth out near-term noise in the data. The basis for this approach is the finding that earnings valuation ratios provide predictive power for long-term stock market returns. Campbell & Shiller, “Valuation Ratios and the Long-Run Stock Market Outlook.” Journal of Portfolio Management 24, 2 (Winter 1998), pp. 11–26.

The long-term mean CAPE as calculated by using Prof. Robert Shiller’s datais 26.48. In January 1921, PE10 was 5.12, the lowest value of any January in the historical period. Meanwhile, PE10 in January 2000 was 43.77, the highest January level in history. It is 26.48 today. well above the reading of 23.00 a year ago, suggesting that stocks remain significantly overvalued. Historical S&P 500 PE10 is charted below.


Source:, using Prof. Shiller’s data

2. DY10. The dividend-price ratio or dividend yield (DY) is another predictor of the subsequent 10-year real returns on stocks, although this approach has its problems. Historical S&P 500 DY is charted below and also suggests that stocks are significantly overvalued today.


Source:, using Prof. Shiller’s data

3. Tobin’s Q. The Tobin’s Q is the ratio of price to replacement cost, which is in many ways similar to book value. See Tobin & Brainard, “Asset Markets and the Cost of Capital,”Economic Progress, Private Values and Public Policy (1977). The most current Q ratio can be calculated from September’s release of the Flow of Funds report for Q2 2011. It is calculated by dividing line 35 of table B.102 by line 32. The historical data is also available on the St. Louis FRED website. However, because the Flow of Funds report is released long after the quarter end, getting a relatively current level takes a bit of extrapolation.

When equity as a percentage of GNP is above-average then total real returns for U.S. equities have a high probability of being below average. When equity as a percentage of GNP is below-average then total real returns for U.S. equities have a high probability of being above-average. Another use for Q is to determine the valuation of the whole market in ratio to the aggregate corporate assets. The Q ratio is a statistical measurement of the market’s value; fair value for Q is 0.65, primarily because capital stock is routinely overstated leading to a larger denominator in the Q equation. See Smithers & Wright,Valuing Wall Street : Protecting Wealth in Turbulent Markets and Doug Short’s excellent analysis here).

Per Doug, the average (arithmetic mean) Q Ratio is about 0.68. The all-time Q Ratio high at the peak of the Tech Bubble was 1.78 — which suggests that the market price was 153 percent above the historic average of replacement cost. The all-time lows in 1921, 1932 and 1982 were around 0.30, which is about 57 percent below replacement cost. Based on the latest Flow of Funds data, the Q Ratio through the end of the second quarter of 2014 was 1.15, up from the 1.05 level I noted a year ago. Doug’s current estimate puts the ratio about 70 percent above its arithmetic mean and 83 percent above its geometric mean, a good bit higher than when we last checked in. By this measure too, then, the market remains overvalued.

4. Market Cap to GDP. Market Capitalization to GDP has been described by Warren Buffet as “probably the best single measure of where valuations stand at any given moment.” It compares the total price of all publicly traded companies to GDP. This metric can also be thought of as an economy wide price to sales ratio. The data here is from theSt. Louis FRED. However, because the data is quarterly, data for the other months have been entered using the prior ratio adjusted for the change in stock prices. As charted below, this metric suggests that stocks are significantly overvalued and overvalued as compared to previous editions of this post in October, 2011, August, 2012, January, 2013 and June 2013 (.96, 1.01, 1.03 and 1.17 compared to the current 1.27).


Source: Vector Grader

5. Bond Yields. Returns on bonds depend on the initial bond yield and on subsequent yield changes. Low bond yields tend to translate into lower returns because of less income and heightened interest-rate risk. As Warren Buffett has pointed out (although he is not alone in this), “interest rates act as gravity behaves in the physical world. At all times, in all markets, in all parts of the world, the tiniest change in rates changes the value of every financial asset. …If interest rates are, say, 13 percent, the present value of a dollar that you’re going to receive in the future from an investment is not nearly as high as the present value of a dollar if rates are 4 percent.” As charted below, despite recent volatility and pressure, long-term interest rates have been generally declining for more than 30 years and remain near record low levels, despite routine calls for a “bond bubble” over the past several years, suggesting that all assets are at risk going forward.


Source: The Big Picture (for a more limited period, the U.S. Treasury data is available for charting here)

These measures all confirm that, from a longer-term perspective, the market remains overvalued and, if anything, somewhat more overvalued than it was when I last ran these numbers a year ago. As I have been saying for a long time (for example, herehere and especially here) – we are (since 2000) in the throes of a secular bear market, subject to strong cyclical swings in either direction. I continue to encourage investors to be skeptical, cautious, and defensive yet opportunistic. I suggest that they look to take advantage of the opportunities that present themselves while carefully managing and mitigating risk, which should remain their top priority.

The Halftime Report

By Robert Seawright, Above the Market

“To err is human,” wrote Seneca. “To persist in it is diabolical” (Errare humanum est, Perseverare diabolicum). As 2014 opened, pundits expected interest rates and stocks to go higher, with more certainty about the former than the latter. They also expected the economy finally to turn the corner after five years of sub-par performance. Now that the midway point to the year has been reached and stocks, bonds and commodities have all posted gains together for the first time since 1993, my ongoing and deeply held cynicism about forecasts and forecasters has yet again been confirmed. In other words, be leery about fighting the Fed, fade forecasts and be sure to diversify.

The halftime scoreboard shows that rather than rising 50bp or so, the benchmark 10-year U.S. Treasury note has rallied by roughly that amount while the long-end of the curve has seen double-digit returns. Global bonds as an asset class have performed admirably (FWDB up 6.45 percent) while domestic bonds are nothing to complain about either (AGG up 3.75 percent). Taking on extra credit risk didn’t really pay, as high yield (HYG) advanced 4.96 percent while investment grade corporates returned roughly 100bp more.

Despite historically high valuations, the S&P 500 index has already jumped 7 percent this year and was up for the sixth straight quarter while small caps have lagged (IJS up 4.16 percent). Going overseas didn’t pay, either in large (EAFE up 4.31 percent) or small caps (EEM up 4.54 percent). Utilities (up 18.65 percent) and domestic REITs (IYR up 16.18 percent) were the leading domestic sectors. The worst was consumer discretionaries (up only 0.6 percent, but still up). Obviously, financial market volatility has remained extremely low.

Meanwhile, the U.S. economy was reported to have shrunk by the highest level since the dark days of 2009 last week (GDP off a whopping 2.9 percent, bad weather or no). If that’s turning the corner, I’m mighty concerned about what we’ll find once the turn is complete. The print was so bad that concerns about recession are back on the table. Moreover, the Citigroup Economic Surprise Index, which tracks how various economic data points are faring relative to expectations, has turned down sharply. Other data points aren’t so negative, as jobless claims have dipped, consumer confidence is up to its highest level since 2008, and a classic Monet sold for $54 million, for example. Accordingly, most economists expect GDP to improve markedly in the second quarter.

As one might expect from a maturing economic recovery, Fed policy is in transition. The Fed will likely continue to taper its bond-buying program – designed to drive investors to stocks – by $10 billion per FMOC meeting, which should lead to an exit from the program altogether by the end of 2014, and begin to raise interest rates by late 2015. That schedule assumes that the economy tracks closely to the Fed’s forecast of near 3.0 percent GDP growth for 2014 and 2015, the unemployment rate declines steadily to roughly 5.5 percent, and inflation moves a bit higher but remains modest at around 2.0 percent. However, since a wide variety of Fed forecasts have been wrong pretty consistently, I see little reason to think the Fed’s forecasting ability will suddenly improve. Remember – fade forecasts.

Among the analysts I respect, such as Seth KlarmanRobert Schiller and Jeremy Grantham, most are concerned about stocks, despite calls among economists for 3 percent GDP growth in 2Q (see below), more stock buybacks and ongoing Fed easiness.


Source: GMO

But, as ever, fighting the Fed is a dangerous proposition indeed.  The cumulative annualized return for the S&P 500 over the last three calendar years has been an astonishing 16 percent and has approached that level so far in 2014 despite an economy that has been tepid at best. That means that money in the market on January 1, 2010 and left there has roughly doubled since. Everybody wants a piece of and nobody wants to be non-correlated to that. Moreover, economic difficulty and stock market weakness are hardly correlated (see below).


Source: Marginal Idea; J. Lyons Fund Management

As a matter of economic (Fed) policy (and in the words of Tomáš Sedláček), we keep shorting stability to try to buy growth. Fiscal policy is a trick, pretending there is demand when there is none. Monetary policy is also a trick, pretending there is liquidity when there is none. Still, we keep pretending (or at least hoping) that the Fed’s new clothes are indeed lovely. It’s bad policy, surely, but there is little reason to try to oppose it with our investment dollars. As Augustine prayed (Confessions, Book 8, Chapter 7): Da mihi castitatem et continentiam, Sed noli modo (a rough paraphrase is “Make me pure, but not yet”). Our investment approach needn’t be consistent with our favored policies. Trick or no, investment returns since 2009 have been both remarkable and real. It’s wise to fade Fed forecasts but fading Fed policies hasn’t worked well.

More specifically, investors with longer-term time horizons can withstand nearer-term difficulty (see below) if, indeed when it happens. It is helpful to recall (as the great investorPeter Lynch pointed out) that far more money has been lost trying to avoid market downturns than in the downturns themselves.


Source: Fidelity

One of the best investment managers out there, Seth Klarman,, who founded the Baupost Group a Boston-based private investment partnership (and whose book, Margin of Safety, sells used for thousands of dollars) , says that we should worry top-down but invest bottom-up. As I have noted consistently in my weekly commentaries of late, there is a lot to worry about in the markets today. Worrying top-down is important because nobody wants to be hurt by some adverse macro, sectoral circumstance. Moreover, the macro environment has to impact the bottom-up analysis – especially as it relates to determining valuation and thus relative value.

But there is still no good way to time the market consistently and investing is required if an investor seeks to outperform inflation and meet longer-term financial goals. Accordingly, in all environments, investors must simply do the best job they can to identify specific, bottom-up opportunities to deploy the available funds. Moreover, the longer the investor’s time horizon, the less important the “top-down” environment becomes. Even so, today’s environment demands caution. I agree with Klarman that the Fed’s adventure into uncharted territory is likely to end badly. What is unsustainable tends to stop. Fantastic deep value investors like Klarman have a long history of being right – but also early. When will this happen? “Maybe not today or tomorrow, but someday,” Klarman writes.

There won’t likely be any sort of signal when the tide finally and inevitably turns. Yet it needn’t be anytime soon either. “Someday: could be a long ways away. Until then, fight the Fed at your peril.

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.