On his first day of Economics 101 in university, Barry Ritholtz realized that the discipline itself was missing something fundamental.
The Wall Street veteran says that when his professor began lecturing, “practically the first words out of his mouth were, ‘We’re going to deal with Homo economicus. Humans are rational, profit-maximizing creatures.’ Five minutes into my first economics class, I raise my hand and say, ‘But humans aren’t rational!’” The professor told Ritholtz he should imagine that they were. “Okay,” he thought, “imagine my grandmother had wheels. She’d be a bus.”
People, Ritholtz knew, tend to do stupid things, like smoking or not wearing seatbelts, despite overwhelming evidence that these behaviours can kill them. He couldn’t accept economics’ central assumption that people are by definition rational, and that they collectively express the order-making invisible hand of the market. Ritholtz went to the registrar the same day, and dropped the class.
Since the time when that contradiction vexed the young Ritholtz, a bridge between economic orthodoxy and human quirk has been erected in the form of behavioural economics, the study of how deeply embedded human traits affect financial decisions. Ritholtz is CEO and director of equity research at Fusion IQ, a research and investment firm with $300 million (U.S.) in assets under management. He is also a prolific writer and blogger—his website, The Big Picture ( www.ritholtz.com), has logged 114 million page views.
Thanks to the bestselling books of academic popularizers such as Dan Ariely, Richard Thaler and Daniel Kahn-eman, the central lesson of behavioural economics—that the brain often misinterprets the information it receives—has been getting a good airing since the 2008 financial crisis. The mistakes include such well-known phenomena as the halo effect (believing that certain leaders can do no wrong) and the sunk-cost fallacy (our aversion to cutting our losses when a project or investment has obviously gone awry).
Behavioural economics’ roots ex-tend to the 1970s, when the Efficient Market Hypothesis—which holds that market prices of traded assets reflect all publicly available information, and thus, because investors are rational, markets are efficient and self-regulating—was in vogue. The EMH became a wrecking ball in the hands of neoconservatives, who used it to justify weakening regulations like the Glass-Steagall Act, a Depression-era law forbidding institutions from combining insurance, investment banking and commercial banking under the same roof. This went on until 2008, when economic carnage—blamed partly on the unregulated repackaging of home mortgage debt—led many people, such as former Fed chairman Paul Volcker, to call into question the omniscience of the market. No rational person with any knowledge of history would believe that house prices would go up ad infinitum, and yet the banks’ profit models depended on that very assumption. So much for Homo economicus.
One of the most fascinating areas of study within behavioural economics is the concept of framing effects. How a question or problem is framed—and, specifically, what future scenarios are presented—affects the kind of solution that our brains will produce. An example chosen by Thaler and Cass Sunstein in their 2008 book, Nudge: Improving Decisions about Health, Wealth and Happiness, is the question of how to encourage people to conserve energy. They write, “Consider the following information campaigns: (a) If you use energy conservation methods, you will save $350 per year; (b) If you do not use energy conservation methods, you will lose $350 per year.”
It’s hardly a surprise that, as Thaler and Sunstein observed, option (b) is a “stronger nudge” and wins more converts to conservation. This behaviour is patently irrational—the outcome is the same, so why should framing the question in terms of a loss or a gain have an effect?—but because of the way our minds instinctively respond to certain scenarios, it works.
Some of our biases are harder to counter than simply changing the frame of the question. In Nobel Prize winner Daniel Kahneman’s Thinking, Fast and Slow, he describes how our brains suffer from overconfidence. This is not so much cockiness—though that’s part of it—as it is our tendency to believe past behaviour to be much more reliable as a predictive factor than we should, and to construct narratives to explain complex phenomena like the stock market even though there are far too many variables affecting a stock’s behaviour for us to really account for.
For example, conventional wisdom holds that the fate of a company is tied to the smarts of its CEO. A CEO’s specific contribution to a company’s overall success is hard to quantify. In order to examine the effect of hiring a rock-star leader to run an existing company, Kahneman compared various pairs of similar firms that had hired CEOs perceived as “strong,” which he defined as one whose strategy had been widely influential. The results suggested that such leaders have only a minuscule effect on a company. “A very generous estimate of the correlation between the success of the firm and the quality of its CEO might be as high as .30, indicating 30% overlap,” Kahneman wrote, noting that the respected CEO would be running the more successful firm in about 60% of the pairs—10 percentage points better than a coin toss.
So, how do you make decisions in light of the fact that, as Barry Ritholtz says, “Our wetware is so poorly wired for capital market investing?” He’s been studying behavioural economics for years, but, unlike many armchair observers, Ritholtz and Fusion IQ have used the lessons of the discipline to inform their investing practice. “What investors don’t seem to get is, this is not like being an accountant or a lawyer or a doctor,” Ritholtz says, echoing Kahneman’s observations that stock markets are too complex to predict accurately. Data amassed by the behaviouralists indicate that experience in stock picking has scant impact on results. “You know, if a lawyer lost half his cases, you’d think he was a terrible lawyer. But if you’re a .400 hitter as a stock picker, hey, you’re an all-star. The way to lose the ego is to say, ‘I am going to be wrong frequently, and occasionally spectacularly so.’”
Another common mistake investors make is to fall prey to what behavioural economists call the recency effect. When a particular investing strategy or market indicator has been successful recently, that is what will come to mind rather than the full panoply of strategies. Unfortunately, complex systems like the stock market produce results for a given action that, more often than not, revert to the statistical mean.
So if the market is largely unpredictable by definition, how do you predict it?
For starters, don’t put too much faith in the predictive power of any one type of analysis. “I use five major metrics: trends, macroeconomic [data] market internals, sentiment and valuation,” Ritholtz says. He then makes a decision based on those factors, while bearing in mind the lessons of behavioural economics. “Here’s the thing I find fascinating: At any given time, three out of the five of those metrics are all but irrelevant.” Market sentiment, for example, is only useful, according to Ritholtz, at the very top or the very bottom of the market.
You also need to set rules for yourself, to combat the sunk-cost fallacy. Most investors know what it feels like to research a company, from its historical earnings down to the size of its factories, and be disappointed when the share price goes in the opposite direction than they had expected. Studies show that it’s hard for our brains to let go when we’ve invested time and/or money in a stock, no matter how much it tanks. If humans were rational, the pain of writing off a loss would be equivalent to the pleasure of an equal-sized gain. But as many investors have already learned, losses are disproportionately more painful to our brains than gains are pleasurable, and many investors sell far too late.
Ritholtz describes Fusion IQ’s moves throughout the fall as a supreme test of his company’s determination. After the firm sold its volatile technology, emerging-market and small-cap stocks at the beginning of August, the S&P 500 dropped almost 15%. Beginning in October, however, there was a five-day rally, and the firm decided to buy back into some of the small-cap names it had dumped. “It had a nice run,” Ritholtz says. “It ran up another 10, 11% from there, and up to 1,300 [in the S&P 500]or so. And then started heading back, and it came right back to the level where we bought, and it was heading through it, so we sold. We basically said, hey, this was a fake breakout, so if we can get out at a break-even and not suffer the drawdowns, we’ll be happy.’”
Even though he says “the gut instinct is, ‘I gotta get me some of this; jump in!’” Ritholtz stands by the strategy he hatched in less emotional times. “I call that the prenup. When you’re first engaged, everybody’s happy and it’s unthinkable that it won’t work out, but at least you know everyone’s objective, you’re not throwing plates and there’s no emotion. You buy any asset class, any equity, you buy anything—you make a decision at that moment, while you’re still objective: ‘Hey, if it does this, this is where I get out.’”
Strategies to combat the emotional turmoil brought on by loss aversion, the natural cognitive disinclination toward any kind of loss, are even finding their way into the sell-side world. Insurance and wealth management titan Allianz has launched its own Center for Behavioural Finance, whose website features a white paper by UCLA professor Shlomo Benartzi that recommends advisers adopt what he calls the Ulysses Strategy, namely having investors and advisers draw up a “Commitment Memorandum” whereby they agree in advance what action would be taken in the event of market moves of, say, 25% in either direction. The agreement is legally non-binding, but it does encourage investors to resist being swayed by loss aversion, particularly in turbulent markets.
For all the doom and gloom about our mental shortcomings, behavioural economics does provide us with one reassuringly universal caveat: that no one is exempt from these irksome biases. You, me, Ben Bernanke and the rest of the human race: We’re all in it together.
Face value: Digitally aged pictures cause people to save more for retirement
If you have trouble conceiving of the financial needs of your older self, you’re not alone. Studies show that the part of the brain that lights up when people think about themselves in retirement is the same one that is activated when they think about a stranger. To bridge the gap, a team of researchers at Northwestern University, led by Hal Ersner-Hershfield, have developed digital imaging techniques that show prospective savers what they will look like at retirement age. Seeing themselves years later significantly increased their willingness to commit more money to retirement savings, as did changing the image so that the face was smiling. Insurance and wealth management giant Allianz is now developing a scaled-down version of the technique for its financial advisers to use.