Biohacking Market Makers: Intro to Neuroeconomic Study

(Shortened for publication purposes)

By Eli Graham

How can market bubbles be anticipated? Is it possible to anticipate them? The

conventional economic way of thinking would typically answer no. After all, typical economic

heuristics define all actors as rational and acting in their own self-interest. With this in mind, is it

possible to anticipate when actors we otherwise consider rational decide to be… not rational? In

an attempt to reconcile questions like this with neoclassical theories, the field of neuroeconomics

was born in the 1990s combining concepts observed in behavioral economics, neuroscience,

game theory, and cognitive psychology. There are many aims of the field, but one of them is

attempting to understand group aggregate behavior as seen in large scale financial markets.

In the last forty years, the level of competition in financial markets has sky rocketed, with

incredible amounts of resources being dedicated to arbitraging away in any potential excess

value from traders, retail or institutional. From using satellite imagery to door-to-door surveys,

investors have to get creative to find an edge in the modern market. There is perhaps a new

frontier for deriving alpha: neuroeconomics and its implications on exploiting traders.

Black box quant trading firms pride themselves on their ability to compile the most data

and make near perfect decisions in order to achieve alpha in hyper competitive markets. The

level at which they are able to predict market trends and close arbitrage gaps is incredibly

impressive. At the core of these operations are traders and software, the former of which

neuroeconomics attempts to understand. In an MIT PhD thesis paper, Dr. John Perry set up an

experiment to test the causal relationship between physiological responses and trading decisions

of some of Wall Street’s most experienced market makers. In the experiment, Dr. Perry

monitored various internal systems within the traders’ bodies including heart rate variability,

internal temperature, and skin conductance. The goal of the study was to discover whether there

was a causal relationship between physiological signals, otherwise described as emotional

responses, and output of trade decisions. The results of the study found that there was an increase

in the predictability of a trader’s decision when taking into account a physiological and financial

model as opposed to soley a financial model. In Dr. Perry’s words,

“The aforementioned results suggest that emotional responses are associated with real-

time processing of (financial) risks. This notion runs contrary to conventional beliefs

regarding rational (financial) decision-making. It has been hypothesized that rationality

entails acting without emotion and that professional traders—of all people—should be

the least likely to exhibit emotion. Yet, there are statistically significant differences in

emotional responses related to changes in cognitive inputs.”

This means that emotional responses to information, in the form of predictive and real-time data,

alter cognitive decisions. Taking into account how traders feel about the information they read

improves one’s ability to predict their decisions versus the information they have on its own.

While Dr. Perry echoes criticism of his peers that the study was conducted on a relatively small

population (it turns out it is quite hard to convince Wall Street traders to let you monitor their

screens and trading decisions while making them wear a bunch of medical devices at work), he

believes that it is nonetheless valuable information.

When playing the zero-sum game of asset trading, modern traders may be able to gain an

edge by not only considering their evaluation of a trade being over or under valued, but also the

emotional state of the trader on the other end of their prospective trade. When engaging in a trade

at a given price, it is true that the inverse decision is being made by some other trader. Any

purchase by one actor is a sale by another. This means that however much research you have

completed, for a trade to complete, someone else is willing to bet the opposite. When looking for

alpha in any market, the study of neuroeconomics would advocate not only for due diligence

upon the underlying trade’s value but also on the psychological state of the trader on the other

side of the transaction.

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