Background
In the context of this chapter, the term neurofinance encompasses all financial applications of neuroscience disciplines, ranging from market microstructure to the behavior of the decision makers that commit to transactions through capital markets. Among practitioners, neurofinance has emerged as an independent field of study in the aftermath of the Global Financial Crisis (GFC) of 2007–2008. The ethical aspects of short-term seeking behaviors faced unparalleled scrutiny as a result of the crisis. In particular, the GFC brought about the need to reassess the essence of decision making and what makes decisions value accretive or not and to whom. Since then, the focus of market participants (e.g., investors, regulators, and the broader investment community) has shifted from the evaluation of short-term outcomes to the assessment of long-term consequences on economic growth, with the ultimate goal of benefiting society at large. As a result, the market participant him/herself goes from being thought of as a pure utility-driven economic agent to a human decision maker. Personality traits, heuristic tendencies, and inner biases take center stage. The commonly accepted assumption of fully rational economic agents comes to question at the same time as new frontiers in academic research blend empirical findings with existing intuition from a wide variety of disciplines (e.g., biology, psychology, chemistry, ecology, and sociology, to name just a few).
For over a century, the founding principle of traditional finance, the Efficient Market Hypothesis (EMH), had postulated the maximization of expected utility measures as a key driver behind individual decision making. New empirical processes, which directly challenge the EMH, continue to be evaluated and tested. Challenging economic theories are nothing new to industry practitioners. Businesses that adopted the computational principles of mathematical finance, as well as its complexities, throughout the 1970s and 1980s found themselves challenged by the myth of full rationality assumptions when behavioral finance studies brought about the principle of bounded rationality (BR) in the 1990s. Coined by Stanford University professor Herbert A. Simon, BR encompasses all the theoretical work and experimentations that deal with “constraints on the information processing capacity of the actor” (Simon, 1972, p. 162).
Today, neurofinance aims to address BR by bringing the economic agent and his/her learning models (or inhibitors thereof) to the forefront of an astounding multidisciplinary field of research. Thanks to advances in computational ability, as well as the theory of decision making coupled with sociology findings, neurofinance promises to have wide implications for industry practitioners. The future of its direct applications has just begun.
Figure 1.
Structure of neuroscience reasoning