What if the mystery of market crashes stems from a simple but total misunderstanding of our own minds? Could everything we think we know about ourselves—intelligence and rationality versus emotion and irrationality—be wildly off the mark? Simply put: yes.
With these words, Denise Shull introduces her radical—and supremely rational— approach to risk. Her vision stems from the indisputable fact that human beings can’t make any decision at all without emotion and that emotion gets the first—and last—word when it comes to our perceptions and judgments.
Shull should know. She started out managing major accounts for IBM and then chose to research unconscious emotional patterns instead of getting her MBA. Next she became a trader and trading desk manager while continuing to study biopsychology.
We are all taught that sidelining our emotions is the best way to make good decisions— Shull declares the converse: emotions inform us. Attempting to control them actually increases the risks we take. Shull advocates treating feelings as data, and she convincingly argues that doing so eradicates the baffling question that repeats itself in our heads after making a poor investing decision: “What was I thinking?”
Through a series of “lectures,” Shull logically but engagingly connects emotions, beliefs, and context to our innate reaction to uncertainty and risk (yes, the two are different). In Market Mind Games, she merges more than 20 years of studying risk decisions into a single, astoundingly effective strategy.
A reasonable approach to emotion is the best and only way to win the investing game. The methods Shull details in Market Mind Games shake the foundation of conventional market and decision psychology. And, most important, they work.
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|Publisher:||McGraw-Hill Professional Publishing|
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MARKET MIND GAMESA Radical Psychology of Investing, Trading, and Risk
By DENISE SHULL
McGraw-HillCopyright © 2012 Denise Shull
All right reserved.
Chapter OneFrom Wall Street to the Ivory Tower and Back
Monday, April 18, 2011, 12:45 AM
Michael rolled his over stuff duffle bag into the taxi queue at O'Hare. He'd stayed an extra day because the champagne powder just kept on coming but that meant he had just barely made it down the mountain in time to slip through the closing doors on the evening's last flight out of Denver. The 80 people now ahead of him combined with the 15 degree wind-chill compelled an audible, "You've got to be kidding!" Getting to ski with his younger brother Tom, while always a blast, drove a hard logistical bargain—particularly when he thought of the econ undergraduates he would be facing on maybe five hours of sleep.
"Oh well," he thought, "next year when I'm back to being the runt on the trading desk, I won't be skipping town for four days just because a blizzard rolls into Aspen."
A decade ago, Michael had been recruited to be a proprietary trader at Schoenberg Trading. He'd accepted against his father's will because in the late 1990s, the market seemed to print money—at least for anyone who understood the momentum game of stocks and because the day-to-day work actually felt to him a lot like chess, something he had excelled at even as a kid. For a few years, it was great. He could wear jeans, the firm bought lunch, and he was only supposed to trade from 8:30 to 11 and 1:30 to 3. The firm provided what were then cutting-edge analytics on the relative strength of each industry group and taught everyone to trade by buying the strong and selling the weak. It worked until it didn't.
Most of the guys learned how to be long stocks but when the Internet bubble burst, they couldn't, for some inexplicable reason, apply the same idea on the downside. The firm closed their Chicago office and in the fall of the 2002 bear market, Michael returned to Chicago University for his MBA. He thought taking on a purely quantitative view of markets would be the best alternative.
After he got to Chicago, however, he found the classes too management focused. He cared about markets. Of course, Chicago as an institution had a long history of market theory; so with a little finagling, he segued out of financial analysis and into decision theory—a PhD track. For a while it felt exhilarating just to be able to cogitate. He had grown up immersed in books and spending his days contemplating models of decision making suited him just fine.
In the aftermath of 2008, however, headhunters surprisingly began to call. He wasn't even sure how they found him. He wasn't big on LinkedIn, Twitter, or Facebook and didn't have anything resembling a raging social life. He turned the first two down flat. He had no interest in pumping out a bunch of data that some portfolio manager or marketing type would use for raising capital but otherwise cast aside. Eventually, however, when the offer clearly included the chance to sit on the trading desk and potentially manage a portfolio himself, he could no longer resist. Inside, he realized he really did want very much to return to "running money."
Michael's father, Richard, predictably had criticized Michael's decision. He had loaned Michael part of the $100,000 tuition and would tolerate slow payback as long as Michael stuck with academia. He didn't approve the first time Michael had gone to Wall Street, and his return lit up something akin to a simmering rage. Richard Kelley believed that speculators abjectly lacked morals and, even though he dealt with hedge funds in his role as chief financial officer at an insurance company, he pejoratively referred to them as "necessary evils."
Finally, through his haze of half-awake thoughts, Michael realized that the people behind him were moving him forward. A bevy of cabs arrived and the line lurched forward—putting him face-to-face with a tall brunette he'd noticed on campus once or twice. Instantaneously weighing the benefits of jumping the line versus humiliation, he summoned his most gentlemanly voice and asked, "Pardon me, but don't I see you around at Chicago U?" It worked.
In the cab, Renee explained her graduate work in the university's Biopsychology Institute. At first, Michael admitted he needed the layman translation of "researching the reciprocity between mind and body all the way down to cellular mechanisms and their ties to behavior and social context." Renee gave it another try not yet knowing herself Michael's reason for being at Chicago U. "Well, look," she said, "for a long time and even today in some circles, not only is the mind different than the brain but the brain is virtually detached from the body—at least in terms of theories about how we think and decide. The work in my department brings all three back together."
Michael, as a decision researcher himself felt intrigued. "Amazing" he said. "I teach undergrads out of the decision research center over on Hyde Street."
"Really? I didn't know we had a Decision Center."
"Well, right back at you" he said with a smile. "I've been here for over eight years and never heard of a Biopsychology Institute!"
"Guess we're even then," she said with a laugh. "So what exactly does this decision department do, anyway?"
"Well, if you read the brochures, they say we study 'the processes by which intuition, reasoning, and social interaction produce beliefs, judgments, and choices.' Most people think we are the behavioral economics department but labeling it as 'behavior' narrows the scope to what seems to me to be just the end result. I mean, what causes the behavior?"
"Exactly," said Renee. "Basically, that's our philosophy too!"
Abruptly, he realized they'd arrived on campus. Michael insisted Renee be dropped off first, and he wouldn't let her give him more than $15 for the $52 fare. "I got to jump the line to ride with you, so we're square," he said. As he stuffed the bill in his pocket, he happily realized her card was sandwiched within the money.
Monday Afternoon, April 18, 2011
With a noontime nap under his belt and a quad Grande Latte at his side, Michael settled into reading the stack of opinion essays he'd received that morning. The first one was entitled, "Markowitz & Beliefs."
Harry Markowitz had won a Nobel Prize for figuring out what back in 1952 was called "Modern Portfolio Theory" and for what some consider the first truly quantitative approach to asset allocation. This title suggested the student had a psychological take on the mathematical approach. "Hmmm ... interesting" thought Michael just as he heard his father's ring tone. Seemingly always at the worst moment, Richard called. He probably only wanted to find out what his brother Tom was up to. When they were kids, Dad always favored Tom, the jock. Michael's GPA never garnered much enthusiasm (or even attention for that matter); but after Tom got cut from the US Ski team and moved to Aspen to patrol, his father rarely, if ever, spoke to him. He used Michael—or tried to use him—as his messenger. Michael hit IGNORE and assuaged his guilt by telling himself he would call him back when he'd finished grading this stack of papers.
Somehow three hours then evaporated and Michael wanted a break. The sun shone through his windows and the temperature outside seemed to have sky-rocketed. As he rounded the first corner on his way back to Starbucks, he stopped into the department office to see if anyone wanted to join him.
"Michael, good to see you! I was just wondering when you were coming back," said Professor Zinnis, Michael's dissertation advisor and one of the bedrocks in the department.
"Say," he continued, "A few weeks ago, I agreed to jointly sponsor a guest lecture series with a professor in the psychology department and I thought, given that it has a Wall Street bent, it would be right up your alley."
"Really? ... what's the actual subject?" said Michael.
"Well, you probably haven't heard of them but we have a department here called the Biopsychology Institute, and a long-time friend of mine over there recommended we invite one of their graduates who runs a consulting firm on Wall Street—a woman named Denise Shull—to speak on what she calls the new psychology of risk, uncertainty, and decision making. It sounded like a provocative topic for the end of the year Friday series, so I went with it."
"That's mildly amazing actually. I just met a woman from that department last night in the cab line. I didn't know they existed! When is it?"
"Well that's the thing, in only a few weeks, so I was hoping you would help get the word out. There is draft flyer on the printer now. Let me know what you think. You've been around here long enough to know what might entice our quirky but lovable geeks to show up for a talk on something other than esoteric models."
"Aha," Michael laughed. "Maybe the angle of a room full of female psychology grads might get some traction." After all, having met Renee, the pitch already worked for him.
Chapter TwoNumbers Look You in the Eye and Lie
Day 1: Special Lecture: A (Radical) New Psychology of Risk Chicago University
May 13, 2011
"So without further ado, I would like to introduce our speaker, Denise Shull," said Michael, as he took a seat beside Renee.
Thank you, Michael, and thank you, everyone, for being here. Let's jump right in.
2 plus 2 equals 4. There are no if, ands, or buts about it. Express it in Chinese and 2 plus 2 does not magically morph into 6, despite the beauty of the characters or the evidence that different cultures learn math in different parts of the brain.
2 and 4 in a different context, however, can mean any number of things. Deceptively, 2 times 2 still equals 4. 2 minus 2, however, equals zero. Go to point two (.2) and you could mean 2/10ths or 1/5th of a whole—as in the answer you give Grandma when she asks how much of her scrumptious gooey pecan pie you want her to cut (you've got four relatives at the table); or, you could mean you have a 20% chance of losing all of the money you risked on a poker hand, a real estate investment, a decision for a new business, or a simple options trade wherein you bought calls on the off-chance AAPL might dip below $320.
Clearly, even in simple arithmetic, the purest of numerical disciplines, any given number only means something in the context of what sits next to it—plus, minus, times.
If a percentage sign sits next to it, well, honestly, despite the reliance on probabilities for betting, all bets are off. When we enumerate chance, we enumerate uncertainty. Unfortunately, the satisfaction we experience from enumeration tricks us into thinking we have waved the magic wand and remodeled 20% into 2 plus 2 equals 4.
Numbers make us feel good. We know we appear erudite, and we privately feel exceptionally smart if we find or have a set of numbers that argues for our point of view. We tend to feel particularly self-satisfied if we possess a set of numbers that appears to prove something that we are the first to figure out.
But have you said or ever heard someone say, "Just because I can"?
It's an idiom and an attitude typically chuckled about behind closed doors, but I'd wager that most of us in this room have either said it your-selves or been tempted to applaud when your best buddy uttered it.
However, isn't the subtext of such a statement, "Well, maybe I should have but probably I shouldn't have but I did it anyway just because I could," this, "I felt like it, wanted to, or thought no one would know"?
And there we have the crux of many matters of human decision making and behavior—perceived consequences or the lack thereof.
We do what we do because we expect the things we want to occur as the result. Likewise, we also don't do what we don't do because we expect that if we did, things would happen that we expect would be, "umm, well ... unpleasant."
Expectations about the future, particularly how we imagine we will feel, serve as the cornerstone for deciding whether or not we drink that third glass of wine, run that mile, or say something provocative to our boss. Now, in each of these work-a-day world cases, we can come very close to a precise prediction about what will happen—we will wake up with a headache, we will feel more energized, or we will suffer grating wrath.
Yet, what do we do when we can't be so sure of the consequences? How do we choose our actions when the information available in the present fails to be enough to know what to expect? (Like say when it comes to predicting whether the value of a stock, bond, or commodity will go up.)
The Seduction of Statistics
Particularly when it comes to markets, we turn to the mechanisms of statistics and probability—those certain kinds of numbers that make us feel we have measured the future, but in reality only deceive us into thinking we know what we need to do. Reality points to a very big gap between where the numbers leave off and exceptional performance begins! Traditional trading education repeatedly advises students to "analyze what confluence of circumstances you are looking for, know what outcomes they have led to in the past and when they re-occur, take the trade." Likewise, if you don't see the same situation, do nothing.
Peter Bernstein wrote in his market classic, Against the Gods: The Remarkable Story of Risk, that mankind's modern times began when we learned to understand, measure, and weigh the consequences of risk. Normally (if there is such a thing), markets—bonds, stocks, commodities—don't all trade in the same direction at the same time. Stocks go up while bonds go down. Markets that appear to not trade with any relationship to one another—something like AAPL and Spanish government debt might be marked at .1. Take the stocks of big USA-based technology companies and it wouldn't be uncommon to find correlations marked at .7 or .8. Offsetting risk in one market simply required being active in another, relatively uncorrelated one.
The MBAs here of course understand this; the psychology gang, I realize that you may or may not.
Yet, no less than the CEO of Goldman Sachs himself called the violent market swings of August 2007 a 25th deviation event. According to the discipline of probability, what we saw with our own eyes could not happen—not in our lifetimes or the lifetimes of all of our ancestors and all of our children, grandchildren, and their great grandchildren. Then a mere 13 months later, markets stunned the entire planet when every single one went simultaneously in one direction—another thing that, statistically speaking, could not happen.
Theoretically, given our 21st-century capacity to capture every minute detail of a pattern (and to react to it within milliseconds), the earlier excruciatingly painful whipsaws of 1929 or 1987 wouldn't re-occur. Yet, in the 21st century, in each successively larger billion-dollar bonfire, from 1997 to 2001 to 2008, the world elite of Bernstein's measurers had indeed measured not only once, not only twice, but a hundred times.
Today in the spring of 2011, the gut-wrenching days of 2008 may be fading from our memories, but one thing is for sure. Despite widespread blame of alleged greedy bankers, it makes no sense to believe that they expected to lose money. It makes no sense that dedicated life-long employees who invested all of their retirement accounts in the stocks of their own companies, BSC and LEH in particular, expected, probabilistically or otherwise, for their companies, monies, and lives to go up in the smoke of billion-dollar bonfires. Indictments of greed are overrated as useful explanations or contributions to solutions.
In fact, many were looking at numbers that had been analyzed every which way from Sunday and that still showed money coming in the door—practically right up until the moment that it stopped. A few outsiders "interpreted" the numbers a different way and made literally billions of dollars. Reportedly, Matthew Tannin of Bear Stearns had a sense—not a number—that caused him to alert his boss to the possibility that the numbers weren't telling the whole truth—numbers that landed them both in court.
Nevertheless, PhDs in fields like physics, game theory, and theoretical math at esteemed firms like Renaissance spend every day dreaming up new ways to slice and dice the latest probabilities hidden in whatever the current mood of the markets seems to be. But you've got to wonder: if it truly was a matter of uncovering the market data equivalent of E=mc2, then wouldn't they have found it by now? Or, doesn't the fact that they keep looking, in and of itself, prove that at best any probabilistic viewpoint is only temporarily relevant? And if only temporarily relevant, how do they detect when the relevance ends?
Logically, if you have a probability that you know will only apply for a limited period of time and by definition that probability tells you that you have some significant chance of being wrong, even while it still applies, how much do you really know?
Excerpted from MARKET MIND GAMES by DENISE SHULL Copyright © 2012 by Denise Shull. Excerpted by permission of McGraw-Hill. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
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