How the Efficient Market Hypothesis (EMH) leads to sub-optimal decision-making.

Whether it’s called the Efficient Market Hypothesis (EMH), Modern Portfolio Theory (MPT) or the Chicago School, this widely used mathematical framework makes explicit assumptions about investors and market behavior. For years now, research from different disciplines has challenged many of these assumptions including: complete/symmetric market information, rational risk averse investors, maximum utility, Gaussian distributions, dividend/debt indifference, and fixed correlations between assets. Moreover, the 2008 credit crisis made it clear that none of the EMH assumptions worked in the ways the theory predicted. Yet EMH and its associated methodologies including Value at Risk (VaR) are still being used extensively. This may in part be due to the lack of a robust alternative and the deep sunk costs in the current IT and compliance systems. It is the considered opinion of a number of quants that there is much room for improvement.

My claim is whatever the degree of revision or refinement, the fundamental assumptions – with all their strengths and all their weaknesses – will continue to decisively blind their users to large “unanticipated effects.” What needs to be recognized is that every form of analysis, every plan of action, every description of the world, or some portion of it, is a simple or complex model of that world. One of many possible alternatives – each of which will be more or less useful, more or less accurate, more or less entrancing to us. Knowing the assumptions of the models we use confers the advantage of knowing when, and how, to apply them. The decision maker can then become strategically decisive.

First, a model is not a copy, just like a map is not what it describes. A model is a description, a diagram, even an object that highlights particular, and hopefully important, features of some phenomena including: key elements, relations, properties and dynamics. A model also hides, or omits, other details as well as other models. A road map won’t show zoning. A stock price chart won’t show employment. Whether it’s a price chart, a money flows diagram, or the description of a risk management process, it’s a model.

With this in mind, let’s restate a couple of the key assumptions of EMH/MPT.

1. Markets are information efficient and complete.
2. Market participants are identical rational decision makers.

When you look out the windows of a skyscraper at the people below, they appear small. Get high enough and they become moving specks. Forget about age, gender, race, wealth, education or anything else individual. These can’t be seen. At this altitude, it’s all atoms. That is, markets are information on the transactions of “social atoms” – also known as Brownian motion. That’s the basis of the Efficient Market Hypothesis (EMH) model. It is the beginning of modern finance with Louis Bachelier (1900) – the first person to model stochastic processes or random walks. And that is what it is: a model.

As mathematical finance giant Robert Merton stated, “At times we can lose sight of the ultimate purpose of the models… The mathematics of models can be applied precisely, but the models are not at all precise in their application to the complex real world. Their accuracy as useful approximations to that world varies significantly across time and place. The models should be applied in practice only tentatively, with careful assessment of their limitations in each approximation.” ­

Of course, this isn’t what we social atoms do. We apply our models wherever they incur an advantage. Which is to say, as widely as possible. And then we forget they are models, and take them to be the world. This happens in every endeavor, every discipline, every domain of knowledge – from the ‘unsinkable’ Titanic to sub-atomic physics (Are there really quarks with color and infinitesimal strings?) to the fixtures of modern finance.

The Efficient Market Hypothesis / EMH is (only) a Model

Some of the slippages between the EMH / mathematical finance models and the world have been pointed out by others. These include philosophical and behavioral (finance) critiques – for example, the use of Gaussian functions, and failure to account for an S-shaped utility curve respectively. Recent research suggests a neurobiological basis for these and other more basic assumptions. These will follow the more obvious ones.

• EMH ‘smoothes out’ data outliers with its Gaussian assumptions.

(Ex. Market crashes and fat tails, which are real phenomena, are omitted)

See Benoit Mandelbrot and Nassim Taleb on extreme events (Black Swans).

• EMH database selection biases results.

Ex. Data sources, data periods, data comparisons, start and end dates, smoothing)

See James Montier and Behavioral Finance, Michael Covel and Trend Following.

• EMH assumption of identical individual rational decision-makers ‘hides’ herd behavior.

(Ex. Financial bubbles as well as normative behavior like managers seeking Beta)

See Irving L Janis and Philip Tetlock (on Group Think), Behavioral Finance (on herds)

• EMH assumption of individual rational decision-makers hides traditional ‘bonds’ between debtors and creditors.

(Ex. Debtor/Creditor known to each other, community, reputation and shaming)

See Charles Morris “The Two Trillion Dollar Meltdown” among sub-prime titles.

• EMH Volatility is a proxy for Risk. Markowitz Optimization: Volatility = Poor returns

(Ex. Trending markets are considered risky, low volatility markets considered safe.             Also, there is no distinction is made between gain volatility and loss volatility.)

See James Montier “Behavioral Investing.”

In the statistical world of mathematical finance, there are only be a few ways to gain an advantage: Knowing what’s going to happen next (insider trading), being faster at taking advantage of arbitrage opportunities (high frequency trading/HFT), trying to build the perfect portfolio (Modern Portfolio Theory), and predicting what will happen next. (More on this later.) These are, in fact, among the principle activities of the investment industry.

Why anyone would use these rational financial models of human behavior is the story of the advantages conferred on its early adopters. Remember, data aggregation and computerization is just a couple of generations old. The lack of prefect/symmetrical market wide knowledge at that time conferred an advantage on those who could recognize arbitrage opportunities and execute them more rapidly. And optimizing a portfolio that reduces loss and stabilizes gains does confer a long-term advantage. Moreover, the “social atoms” modeling was, and is, highly computable, so it fit with the automation trend of the times. And there are other, albeit social, advantages of making finance mathematical. Academics, equations and the resulting spreadsheets and charts and published projections ‘professionalized’ the activities of bankers, brokers, traders, financial planners and others – infusing them with a credibility and seriousness that had previously been lacking.

Which makes it all the more ironic that it was these very human ego gratifying advantages for invoking EMH that the EMH model could not see as they were outside of the model. And there were more of these human characteristics that were not accounted for.

• EMH assumption of independent individual rational decision-makers could not account for local optimization of a system – in this case, company caretakers/managers colluding.

(Ex. Fraternities of CEOs and Boards of Directors, Regulatory Capture)

See Barry Ritholtz “Bailout Nation” and Andrew Ross Sorkin “Too Big to Fail.”

• EMH assumption of risk averse decision-makers and necessity of Risk Premium

(Ex. Higher returns do not necessarily require higher risks; carry trades, etc.

Some higher returns do have higher risks. This is confused by investment firms:             “Higher risks = Higher returns” as in “What is your risk tolerance?)

See most any investor risk questionnaire offered by any investment firm.

Finally, the deepest and most obvious assumption of the EMH/mathematical finance model is everything is about numbers. This would seem like a perfect fit given money is counted. The thing is, all the assumptions that people have about numbers and counting come along with them including: Numbers are definite. There are right and wrong answers. Projections and performance models have some basis in exact numerical facts and are calculated accurately by equations. These ideas affect the framing of risk with unanticipated effects.

• EMH CAPM of Alpha and Beta makes normal trading variance into tracking error.

(Ex. EMH-based risk managers think that losses (below Beta) are errors in the                 trading system rather than normal variance in trading (probabilistic outcomes).

A predictable conflict breaks out between the traders and the risk managers.

• EMH assumptions of advantages result in examining & acting on shorter time frames.

Because EMH equations can be computed on shorter periods of time, they are.

(Ex. Quarterly earnings and even shorter term arbitrage (HFT) becomes the norm.)

• EMH assumptions of limited arbitrage advantages result in many attempts at prediction.

(Ex. While EMH & IT were being developed, actual edges/advantages were identified.

Now new edges/advantages are sought with better, faster data and/or execution.)

As well as the opposite:

• EMH assumptions of limited arbitrage advantages result in new products/revenues.

(Ex. Since markets are efficient, financial institutions make money from ‘advice,’ structured products and fees.)

Thinking of this in terms of mental processes, numbers are models of distinctiveness, and with that, taken as equivalents for certainty. In our minds, the number 1 is distinct from the number 2, and 10 very much from 10,000. We reveal this when we say things like, “The numbers don’t lie.” This clarity carries over to their representation on a page or spread sheet. We say things like, “It’s all there in black & white.” Black and white is what numbers typically look like on a page of paper or a screen, but it means much more to our minds. The neuro-biology of our brains makes contrast binary. This is different from that. “It’s clear cut.” Thus we are seduced by the fact of there being numbers that claim to tell us what the risk of something is whether it’s VaR or some other measure whether they do or not. We are calmed by this misplaced certainty that we are doing the right thing. We relax. This is known as the ‘Illusion of Control’ – which predates Behavioral Finance. We not only don’t control the risks, we don’t even know what they are, while we continue think and feel we do.

• EMH MVO emphasizes information measurement and production over decision-making.

(Ex. VaR & other risk management protocols address our needs for certainty more than devising effective risk management processes.

• EMH cannot account for how an individual’s sense of safety can actually increase risk.

(Ex. VaR – risk managers see the number everyday and nothing happens = safe.

A 1% chance looks so small even though it means 2.2 times per business year.

Better built cars/financial models increase speed/leverage while felt risk remains constant.)

These (mostly) unintentional misuses of mathematics mislead investors, investment firms, risk managers, traders and other financial industry players at every level. They do not know what they think they know. They are not measuring what they think they are measuring. So, they are not making decisions on what they think they are making decisions on. While, almost all around them, it looks and feels like they do.

I think Heidegger way over estimated the man/language relationship – at least how it is currently configured. It seems to me most people are simply oblivious of the language they are using. For example, as it is that time of year, take the phrase “New Year’s Resolutions.” Most of the people making them do so in the form of proclamations, not resolutions. They are likely to protest as proclamations bring to mind tri-corner hats, parchment, and calls of “Hear ye, hear ye.” Yet this is for the most part what most people do, even if only in their own minds. They may insist they mean resolution as in “firmness of purpose” and “definite or earnest determination,” and my question is, of/for what? It appears to be to try and do what did not work the last (x number of times) they tried it.

If language were a thoughtful master of men (and women), we servants of language might have seen that contained within the word “resolution” is the idea “re-solution.” Which is what is really needed: a new solution to our situation rather than a re-dedication to an old one. After all, you clearly already have the resolution (as in determination/motivation). What you want/need are New Year’s Solutions or better stated, New Solutions This Year. Repeat that idea in your mind for a minute. Does it take your thinking in a new direction? While this is not necessarily a solution in itself, (individual results may vary), conceiving of something in a new way necessarily changes it. With sufficient changes, entirely new qualities emerge.

How about taking an etymological (word origins) approach to the word “resolution”? It comes from the 15th century Latin resolutio meaning the “process of reducing things into simpler forms.” So a New Year’s Resolutio would be a process, not a declaration, an investigation, not a proclamation. Instead of saying “My resolutions,” as if they were things among your many unused possessions, you would investigate what your disliked habit, or lack of a desired one, is made of. Maybe objects, actions, images, ideas, emotions or some combination of these. Find out. Also, what works (and what doesn’t)? What is it in its simplest form? What does that point to as next to do? Notice how this shifts your attention. In this process, you become a kind of scientist, investigator, detective. Try out these different roles (and others). They will increase your perspectives.

Taking the etymology back further, the origin of resolutio is the Latin word resolvere meaning “to loosen, undo, settle,” and the root of that is solvere meaning “to loosen, free, release, dissolve.” The reader has undoubtedly noticed the word “solve” in this root. How does doing a New Year’s Solve change your thinking in contrast to a New Year’s Resolution? Moreover, what comes to mind thinking about loosening a disliked habit instead of resolving to overcome it? Or releasing a desired habit into your life instead of trying to force it into existence? Each of these are simply different ways of conceiving of ideas, yet what a difference. Keep in mind that a familiarity with one does not rule out another, nor make it any more useful or truthful (though you are unthinkingly inclined to do so). That is, you need to actually engage in resolutio to experience the resolvere.

Some might describe this as “word magic,” and in a sense they are right. One source of our human ability to adapt and change is to reconceive existing ideas by re-languaging them – whether they are considered difficulties or desires. Yet in our everyday language, we tend to use the most common, conventional, and convenient terms. An advantage of this is we feel we can communicate with and understand each other. A disadvantage of this is that our thoughts, if they can actually be called that, are mostly like everyone else’s thoughts. (Except for those unthinking troglodytes over there. We are exactly the opposite of them.)

If language were truly our master, we would be guided to the processes that find the simpler form of things and allow us to loosen, undo, release and dissolve our difficulties and fulfill our desires. Yet we are not even the masters of ourselves, as our annual New Year’s Resolutions evidence. On the other hand, as the cliche goes, in this brief exploration of the word “resolution” you very likely experienced a new thought, perspective, or additional idea about your New Year’s Re-solutions. Whether this has released something, freed up your thinking, or simply loosened a few conventional ideas, it is a demonstration that we can, if we are interested and willing to make the effort, make some significant use of language.

So, re-solve to have a Happy New Year!

PS – If you want a do-over, or need more time, the next New Year is January 31, 4712           (That’s 2014 to you Gregorians). Year of the Horse, of course.

Fair enough. Experienced traders (and investors) know they need more than one skill to succeed. Moreover, as Robert L. Hagin wrote in Investment Management (2004), “The skills that lead to success in most human endeavors are not necessarily the skills that lead to investment success.”  These unusual skills are typically referred to as “markets, money and mind,” or slightly more specifically, trading/investment strategies, money management and psychology. Though many market wizards have written that mastery of one of these areas does not substitute for skills in another, traders (and investors) alike almost always take them one at a time, and almost always start, and often stay, with market indicators.

The initial obsession with market indicators usually takes the form of price charts in a few time frames with several standard types of Technical Analysis. Some form of moving averages are a favorite. What could be easier? Especially in contrast to the efforts involved in learning something as comprehensive as Fundamental Analysis or as complex as Probability Theory. This is the knowing/comprehensible question raised in the first couple entries. Because we can look at charts and know something, we have a wonderful warm feeling that fogs over the fact this is only one way to look at whatever it is we think we are looking at.  What Daniel Kahneman (2011) calls “What You See Is All There Is (WYSIATI)”. Attention quickly settles on a few markets, charts, timeframes and indicators – often selected because of their recent market visibility and/or someone’s recommendation. The time spent trading these few markets and indicators is emotionally absorbing, and so it feels like real effort, but is not actually systematic or effortful enough to the extent of skill building.

Shorter time frames, measured in minutes, are more appealing because they fit our human sense of significant (price) action. In these constraints, money management is merely a matter of account size. A small account holder thinks he can deal with volatility by jumping out, not because it is an effective time frame or trading strategy. These defaults in market indicators and money management have several knock on effects. Over trading, in terms of frequency and amount per trade, becomes common. Less apparent, and perhaps more important, these initial defaults begin to become the limits of the trader or investor’s understanding and ability to interaction with the financial world. Worse, they don’t even realize this, and apply their partial knowledge until their capital is gone.

A quote being attributed to someone famous for being smart is supposed to make us think it is profound. The juxtaposition of rhyming opposites – such as in the Einstein quote – has been found to increase our feeling that it is true. Thus, the replacement over time of a rhyming misquote for the original. Authority, poetry: no need to engage any critical faculties. Except its assertion – “The most incomprehensible thing about the universe is that it is comprehensible” – is utterly wrong.

Any life forms that evolved in this world had to make ongoing sense of some portion of it. As our ancestors evolved over the millennia in this world, they had to comprehend some portion of it in order for us to be here now. The life forms that found it incomprehensible are extinct. (Or there is the divine argument; the Creator would not deceive his most favored creation.)

Which still begs an unexamined assumption. In what sense does our knowing/comprehension correspond with this world?

“It is even a difficult thing for him to admit to himself that the insect or the bird perceives an entirely different world from the one that man does, and that the question of which of these perceptions of the world is the more correct one is quite meaningless, for this would have to have been decided previously in accordance with the criterion of the correct perception, which means, in accordance with a criterion which is not available.” – Friedrich Nietzsche (1873) On Truth and Lies in a Nonmoral Sense

I am not actually a fan of Nietzsche. (This is the Availability bias. So far, you have only seen quotes from Einstein and Nietzsche, and depending on your motivated reasoning are inclined to opinions of me on this matter.) Except I quoted this essay because it is 140 years old. My point is that these are not new ideas. I could have used other examples. Even the Behavioral Economics research which substantiates and elaborates (considerably on) these earlier insights dates back as much as 50 years. So, why is it most of us don’t know about it?

And your likely answer is the answer. It might be, “I don’t care about philosophy or physics, or what a bird sees, I’ve got trades to make/investments to manage.“ True enough. And who are you making those trades?

Here is a more recent version of the above paraphrased from the work early systems thinker C. West Churchman.

A modern organization is a hierarchical system made up of several levels with different forms of inquiry and rationality. Solving problems (which involves comprehending them) requires knowledge of these levels and their methods. These are likely to include: workers, managers, engineers, scientists, economists, lawyers, (formal or informal) politicians, and more.

Again, you might ask, “How does that relate to me?” For trading and investing, the financial systems (for there are more than a few) are made up of participants and perspectives that include: banks, brokerage, insurance, businesses, funds of every kind, financial instruments and products of every kind, analysts of every kind, advisors of every kind, lawyers, salesmen, accountants, and oh yes, individual traders and investors on this incomplete list. What is your role as a market participant and what perspective does that offer you? Whatever it is, it is as limited as in the man, insect, bird example, or the worker, manager, engineer example. Or to put it another way, any trader or investor who thinks his brokerage firm is looking at the market the same way he is doesn’t understand the business he is in.

So, we know what we know, and we don’t know what we don’t know, and that’s the way it will always be. Except that does not excuse not wanting, even needing, to know more, while at the same time holding what we know as lightly as we can. How can we do that? An actual beginning would involve questioning the authority-based true sounding givens, getting a perspective on where you are in the overall system, and increasing the kinds of (real and imagined) experiences you have – as you have just done while reading this.

The quote previous attributed to Albert Einstein is inaccurate even though it is the one you will find in an Internet search. The actual quote, from his essay entitled Physics and Reality (1936), is “the eternal mystery of the world is its comprehensibility.” It is clear from the context and quotation marks that he was referring to someone else as the author.

I could have easily edited that initial quote away and no one would have been the wiser, but it is instructive of what I am attempting to accomplish here. It points out that what we, including me, think we know may not be so. And that a bit more digging – something we are often disinclined to do – can reveal entirely new knowledge. In this case, that the meaning we make of something is often not at all what the author intended.

For example, Stephen Hawking and Leonard Mlodinow (2010) concluded from that quote that, “The universe is comprehensible because it is governed by scientific laws; that is to say, its behavior can be modeled.”

Whereas Einstein on the very same page of his essay states,

“In my opinion, nothing can be said concerning the manner in which the concepts are to be made and connected, and how we are to coordinate them to experiences. In guiding us in the creation of such an order of sense experiences, success in the result is alone the determining factor. All that is necessary is the statement of a set of rules, since without such rules the acquisition of knowledge in the desired sense would be impossible. One may compare there rules with the rules of a game in which, while the rules themselves are arbitrary, it is their rigidity alone which makes the game possible. However, the fixation will never be final. It will have validity only for a special field of application.”

Note: Einstein wrote that “nothing can be said” as to how our sense experiences and concepts are made or related to each other. Instead, he uses the metaphor of a game with rules wherein the “scientific laws” of physics are the rules – which are never final and “will have validity only for a special field of application.”

As this blog is entitled Higher Level Trading, here is an explanation of the analogy. It is our all too human tendency is to take something cleverly phrased as true instead of examining it further. Once something is taken as true, even the best and brightest among us (see above) are more inclined to justify it rather than question it.

A higher-level trading strategy is to resist the urge to explain what you cannot, and instead figure out what has to be there for the system to produce what it does. In both physics and markets, this can be summarized as a statement of a set of rules. Rules are related to games (among other ‘things’). That Trading is a Game is a well-worn metaphor among traders. Games have fixed rules – though they turn out to be somewhat flexible and not always enforced. Game rules can and do change. More important for our purposes, a set of rules is valid only at a specific level of play. Some examples in trading, from shorter time interval to longer, include: high frequency, scalping, swing, position, seasonal, and macroeconomic. Analogous to physics, above or below a given scale/level of play, and a different set of rules apply. Traders unaware of this won’t know their own level of play – how could they – much less what game level they are playing on. The same is the case for most investors.

This blog will explore what these levels are, how they work, and how to work them.