Chapter 20 – Neurofinance

Introduction

In this book we have argued that cognition and emotion are powerful influences on people’s decisions. Traders are, of course, no different. This chapter begins by considering what we know about what sets a successful trader apart from other people. We have all contemplated the oft-debated question of nature versus nurture in explaining whether a person thrives or fails. In this final chapter, we further investigate where choices come from. The evidence suggests that there are both environmental and biological foundations. The chapter begins in Section 20. with a discussion of expertise, namely, what makes a skillful trader? Cognitive skills are honed through practice and repetition, but emotion also has a significant role. Next, in Section 20. 3, we turn to the emerging field of neurofinance. Using imaging technology, researchers are contributing to our understanding of how people make decisions. In Section 20. 4, we describe some of the insights recently provided by neurofinance researchers. These researchers have found that cognition and emotion have complementary effects. Traders whose emotions appear to be in balance perform the best.

Uncertainty and risk are experienced differently by our brains, as are gains versus losses and risk versus return. The chapter concludes in Section 20. 5 with some practical advice.

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Expertise and Implicit Learning

Consider the following situation. You are at a large concert and run into a good friend, Molly. Of course, you recognize her face immediately. Now think about this. What if, instead, you know Molly is at the concert but is seated across the venue. The friend you came to the concert with, Amy, is going to look for Molly, but the two have never met.

You do your best at describing Molly to Amy. What’s the chance that Amy will be able to identify Molly among thousands of concert goers? Not too likely. Much of what we know we cannot describe in words. A face is a very complex thing, and we simply do not have enough words to explicitly describe one particular person very accurately. Language is categorical, whereas the distinguishing features of two similar faces may be fuzzy. Some cognitive scientists assert that people have knowledge that they cannot verbalize, referred to as implicit learning or tacit knowledge.

Brett Steenbarger argues that traders also have information about markets that they cannot adequately describe in words. Like a human face, markets are probably more complex than the language we have to describe them. Does this mean we need a finer grid with which to describe markets? Or, does this view suggest that we need to better understand how traders make decisions? Excellence in most fields requires expertise. How do we define expertise? Usually we think in terms of relative performance so that those at the top of their game are considered to be the experts.

Because of tacit knowledge, an expert chess player or pro football player often knows instinctively what the best move is, perhaps without any cognitive evaluation whatsoever. Recall in our discussion of the foundations of emotion in Chapter 7 that psychologists believe that emotions can develop completely independently from cognition. In other words, you can feel fear without first cognitively recognizing what is making you fearful. While observing a market, a trader may instinctively know the move he wants to make.

Steenbarger notes that in many instances traders will make similar buy or sell decisions and then, ex post, provide very different descriptions of the information that led to the decision. The traders saw the same information, acted the same way, but understood their behavior quite differently. Perhaps a trader makes a decision based on instinct with no preceding cognitive evaluation. Afterward, the trader generates an explanation that is cognitively consistent with his expectations. Steenbarger argues that “the successful trader feels the market but does not become lost in those feelings. Studies of expert athletic performers have reached similar conclusions. For example, one study argues that “emotions, and the capability to regulate them effectively, arguably account for a large portion of the variance in athletic performance. ” In the trading domain, an expert trader often has a gut feeling about a particular situation but remains in control by taking careful, deliberate action. Does this mean that trading expertise is innate and cannot be learned? Reading the information in a market could be like understanding a social interaction. Some people are just better at it than others.

While some level of innate ability is probably requisite, the evidence suggests that expertise is finely honed. Not too many of us would believe that a professional quarterback spent his teen and early adult years watching football on television while sitting on the couch eating chips. Knowing the rules of a game does not make you good at the game. Practice and repetition are common ingredients across successful experts. For example, accomplished violinists spend, on average, 10,000 hours practicing. Successful traders also devote a lot of time to practice.

Learning they are able

This practice gives them the ability to connect what they know about a market to the action they should take. Through implicit learning they are able to make better and more efficient decisions. A day trader who spends hours, or even minutes, evaluating a current market circumstance before making a trading decision will certainly find it difficult to succeed. 20. 3 NEUROFINANCE While we know that practice is necessary to hone any skill, unlocking the mysteries of the brain is an important key to understanding how to promote the development of expertise in any realm, including investing.

Are evolutionary theorists correct in their contention that our basic emotions have evolved to promote the survival of the species as we discussed in Chapter 7? Do expert performers have innate characteristics, or can anyone develop expertise in trading? Neurofinance and neuroeconomics use neurotechnology to examine how the brain behaves while a person is making financial and economic decisions. In these new and growing fields, results from economics, finance, psychology, and neuroscience provide the basis for further investigation.

Neuroscience uses brain imaging, as we described in Chapter 7, to understand brain activity and how the brain works. With this technology, scientists can actually measure emotional response. The potential of the technology has not gone unnoticed by practitioners. In fact, Jason Zweig, senior writer for Money magazine and guest columnist for Time magazine and cnn. com writes: I’ve been a financial journalist since 1987, and nothing I’ve ever learned about investing has excited me more than the spectacular findings emerging form the study of “neuroeconomics. Thanks to this newborn field … we can begin to understand what drives investing behavior not only on the theoretical or practical level, but as a basic biological function. These flashes of fundamental insight will enable you to see as never before what makes you tick as an investor. Investors who better understand “what makes them tick” will be better prepared to make good investment decisions. It is important to understand that neuroscience is not simply interested in mapping out parts of the brain. Instead, by looking at how the brain reacts during various activities, scientists can understand how the brain functions and solves problems.

We will better understand the mix of cognitive processing and emotional responses. Which responses are controlled and which are automatic responses? These insights will allow economic theorists to improve models of decision-making, as well as investor education efforts. Recall from our earlier discussion of the brain that automatic and controlled responses are associated with different parts of the brain. Automatic responses often stimulate the amygdala, whereas controlled responses activate the forebrain (or prefrontal cortex). Using imaging technology, scientists can observe the areas of the brain that are activated during a task.

In Chapter 7 we also talked about Damasio’s studies of the behavior of brain-damaged patients. The patients were emotionally flat due to frontal brain lobe damage, and Damasio concluded that decision-making and emotion are intertwined. Though studies of braindamaged patients can be informative, brain imaging technology allows more control so that research can be conducted with greater precision. Neuroscientists are making great progress on brain function, and, as a result, researchers are proposing new models and theories that better incorporate aspects of psychology, including emotion.

Insights From Neurofinance

Neuroscientists have investigated a variety of questions related to financial decision-making. Several studies have lent insight into the forces of emotion on trading by studying the physiological characteristics of professional securities traders while they were actively engaged in live trading. In one study significant correlations between market movements and physiological characteristics such as skin conductance and cardiovascular data were reported. Differences were also detected across traders, perhaps related to trading experience.

Another study looked at whether emotion was found to be an important determinant of a trader’s ability to succeed in financial markets. It was found that those whose reaction to gains and losses was most intense had the worst trading performance, suggesting the obvious need for balanced emotions. Brain imaging has been used as experimental participants have made risky choices. This research indicates that how gains and losses are both anticipated and realized is likely to differ inasmuch as different regions of the brain are activated.

When gains are anticipated, a subcortical region known as the nucleus accumbens (NAcc) becomes active. This region is rich in dopamine, a substance that has been associated with both the positive affect of monetary rewards and addictive drug use. The fact that this region is only active during anticipated gains (but not losses) lends plausibility to the differential experiencing of gains and losses in prospect theory. Other brain imaging research indicates that what might lie behind ambiguity aversion is the fact that risk and uncertainty are experienced in different ways.

Recall in Chapter 1 where we discussed the distinction between risk and uncertainty. With a risky choice, the person can assess the probability of the outcomes, but under uncertainty the probabilities are unknown. The distinction is important here because the brain may evaluate a choice in a risky situation differently from a choice when one faces uncertainty. Research indicates that when facing uncertainty the most active regions were the orbitofrontal cortex (a region integrating emotion and cognition) and the amygdala (a region central to emotional reaction).

In contrast, when facing risk, the brain areas that responded during their task were typically in the parietal lobes so that the researchers concluded that choices in this setting were driven by cognitive factors. In sum, uncertainty appears to be more strongly associated with an emotional response, while risk leads to a cognitive reaction. It has been suggested that when times becomes more uncertain (for example in 2008, as was described in Chapter 14), the inability of investors to properly assess the distribution of future returns leads to their moving from rational deliberation to a primarily emotional response.

The result could be widespread unwillingness to hold risky assets in turbulent markets, a tendency that can only exacerbate market declines. A neural test of myopic loss aversion has also been conducted. A group of patients with brain lesions on areas known to be associated with the processing of emotions were compared to a control group. The former group was significantly more likely to take on risk than the control group. Further, the lesion group exhibited greater consistency in their levels of risk aversion. In other words, those with a reduced capacity for fearful responses behaved in a manner more in line with expected utility theory.

Another study focused on how decision-makers’ brains reacted to varying levels of risk, rather than on learning or expected values. Using a gambling game, expected values and risk were varied while participants’ brain activation was monitored. As is typical in finance, rewards were measured using expected payoffs and risk using the variance of payoffs. Interestingly, the researchers report that brain activation varied in both time and location for reward and risk. Brain activation in response to rewards was immediate, whereas brain activation in response to risk was delayed.

Time and location of activation is important because if we can separate the effects of risk and reward in the brain, researchers can further investigate how changes in risk perception affect decision-making. For example, they could examine how misperception of risk and cognitive difficulties contribute to less-than-optimal behavior.

Expertise and Emotion

Research indicates that understanding neural responses will help us to gain insight into some of the puzzles we have talked about in this book. In addition, there are important implications for trader education.

We are all familiar with the old adage that “practice makes perfect. ” In order to gain expertise, it is important to know the rules of the game, so reading up on investing is not a bad idea. But, at the same time, much practice through many simulations under divergent market conditions will promote better decision-making while trading. But, does it pay to become an expert? While we know that many long hours of studying and practice are required, is this effort sufficiently rewarded? There is evidence that this question can be answered in the affirmative for financial practitioners.

One researcher constructed a “differential reward index” as the income for a specified percentile divided by the median income for each occupation. This measure allows us to differentiate high average income from high income for those whose expertise is greatest in a particular profession. For financial and business advisors, including stock brokers, earnings are related closely to achievement. At the 90th percentile the differential reward index was 3. 5, indicating that the top 10% earned 3. 5 times more than the median income level.

In fact, this was the largest observed value for the differential reward index across all occupations studied! Thus the evidence suggests that the benefit of becoming a skilled financial advisor may far exceed the cost. So how can one become an expert? Researchers have concluded that tacit knowledge is an important predictor of success in business as measured by salary, rank, and the level of one’s company (e. g. , whether it is among the top 500 in the Fortune rankings). Practical knowledge, or the ability to gain tacit knowledge and turn it into a good strategy, is a function of a person’s environment and ability.

Thus, with a certain level of competence, hard work can be translated into success. A successful trader, nonetheless, should always remember that emotion is critical to the outcome. We have argued throughout this book that emotion can enhance decision-making. Previously cited evidence suggested, however, that traders are advised to be wary of intense emotional reactions. Another recent study used neuroimaging to examine how decision-makers’ brains responded while playing the ultimatum game described in Chapter 11.

When unfair offers were rejected by the responders, the investigators reported significant increases in brain activity in the anterior insula, a brain area associated with emotion. Recall that even offers that are viewed as unfair should be accepted by a responder who cares only about increasing her earnings. Thus, traders are advised to exert their cognitive skills when experiencing a strong emotional reaction in order to overcome the tendency to react emotionally, just as a responder in the ultimatum game who is aware of his emotional response is well advised to accept an offer even if it seems unfair.

Emotional responses and cognitive evaluations of risk can be quite different. Think about how many people perceive the risks of automobile and airplane accidents. Though riding in an automobile has been shown to be the less safe alternative, often an emotional response plays the dominant role, which may keep some people off airplanes.

Chapter Highlights

1. Expertise is defined in terms of relative performance so that those at the top of their game are considered to be the experts.
2. Implicit learning reflects knowledge that cannot be described using language.
3. Experts have developed implicit knowledge that enhances performance in their particular domain.
4. Neurofinance uses brain imaging technology and results from economics, finance, and psychology to better understand how the brain works.
5. Physiological differences exist across professional traders, and emotion is an important determinant of a trader’s ability.
6. Measured brain responses to changes in risk and reward vary in both location and time of activation.
7. Practice is necessary to excel in trading, and good traders may make decisions based on gut feelings, while at the same time ensuring that they control their emotional responses.

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