Introduction
Financial decisions are life-shaping ones, understanding the neural mechanisms behind them has recently gained momentum creating a new field of research. It aims to improve the micro foundation for financial decisions, shed light on the neural substrates that drive agents in various situations in the financial markets, like investing patterns, saving or spending decisions, managing asset valuations, investing in corporate bonds, through a combination of economics, neuroscience, and psychology. Several scientific studies confirmed that a bulk of our financial decisions are made through our automatic minds ie, subconscious emotions.
Multifaceted Finance
Finance studies money and markets starting from the interest rate charged on the savings account to stock markets to the impact of new tax laws on a country’s economy. When financing options are uncertain and risky, traditional finance examines the development of prices and the best allocation of economic resources. A housing market bubble is a tell-tale sign that investors are unable to rationally evaluate and incorporate information into their financial decisions, thus violating a fundamental assumption of traditional finance. Consequently, behavioral finance emerged to empirically study and account for these violations. Incorporated insights from psychology and sociology demonstrated that emotions, psychological biases, stress, and individual differences influence financial decisions, making researchers go a step further to investigate and find whether incorporating neuroscience findings could improve existing models.
Neurofinance incorporates noninvasive measures of neural and physiological activity to explain how these confer differences in financial decisions. Neurofinance attributes to two major goals; unraveling the neurobiological factors affecting the behavior of financial market participants, and explaining the apparent inability of standard finance theories by providing physiological explanations.
The Mechanism
Neurons are the building blocks of the nervous system responsible for the transmission of electrical and chemical signals within our body. Among its various types, the sensory neuron helps in carrying information to organs like the eyes or ear helping in cognitive thinking. Understanding the 86 billion networks within our brain is quite an arduous task!
Our brain reacts in expectation of a reward where the brain and behavior are not balanced and matched with the conventional theory of finance. Human behavior is the result of the fluid interplay between controlled and automatic processes. The neoclassical approach falsely construes many behaviors as a result of only cognitive deliberation. Among the various factors contributing to the differences are:
- Genetics: Polymorphisms of genes modulating the dopaminergic and serotonergic systems to elucidate the underlying investment behavior. DRD4 gene, dopamine receptor was mapped as pathological gambling gene or in financial risk-taking healthy humans. Carriers of 7-repeated L-allele have a higher risk appetite while the DATI gene, dopamine transporter shows higher risk aversion. Short-allele carriers are less financially risk-taking humans and increase loss aversion.
- Anatomy: Risk-taking behavior is related to some extent to the gray matter volumes of the brain networks including the anterior insula, ventral striatum, and the posterior parietal cortex. Risk-averse individuals showed altered grey volume, and lower levels while risk-loving contained higher grey volume. Subjects with high loss-aversion have higher gray matter volume of the centromedian amygdala nuclei compared to subjects with low loss aversion.
- Brain activity and functional connectivity: While anticipating an outcome of a high-risk gamble, risk-seeking subjects had lower activation within the ventral striatum and anterior insula compared to risk-averse subjects. Processing of outcomes of risky choices, risk-averse subjects showed reduced risk prediction error signals in the anterior insula, the inferior frontal gyrus, and the anterior cingulate. While financial decision making, increased activation of the anterior insula was associated with increased harm avoidance.
- Hormones: Testosterone response played a role in optimizing long-term performance in high-frequency trading. ‘Winner effect’ causes an increased level of testosterone among winning males while the loser experiences a drop leading to a higher probability of subsequent winning and increased risk-taking on the next round of trading sometimes leading to excess bidding and thus overpricing. Treatment with testosterone resulted in increases in three measures of asset overpricing: amplitude, market value amplitude, and duration. Both testosterone and cortisol administration was not associated with changes in low-risk stock investment and women.
- Gender Difference: On average, women tend to be more risk-averse and less overconfident compared to men.
- Risk-Taking: Men tend to buy riskier stocks than women, though no differences appear between mutual fund managers regarding risk and fund performance, social situations but less willing to engage in potentially life-threatening activities. Women with a low level of knowledge in financial matters feel less competent when lotteries are framed as investment decisions therefore particularly risk-averse.
- Overconfidence: Women finance professionals are as overconfident as men although women were more likely to shy away from competition in hypothetical tournament situations. Although women tend to be less optimistic about the probability of large gains and less risk-tolerant to losses than men, this behavior does not equate with a higher level of overall risk aversion.
- Ambiguity tolerance: Female investors weigh risk attributes, such as the probability of loss and ambiguity, more heavily than their male colleagues and tend to emphasize risk reduction more than men in portfolio construction.
- Other factors: Stress amplifies gender differences in behavior during risky decisions, such that males take more risk and females less risk under stress.
Conclusion
Neurofinance and its findings present a unique opportunity for investors and institutions to not only redefine rationality but to rethink its impact on financial decisions and investment behavior. Understanding which computational models of decision-making map best onto underlying neural activity could be used to facilitate consumer choice and could find an application in, user interfaces in complex and large purchases.
