Human brain and financial behavior: a neurofinance perspective

• Published date: 11 November 2019
• Date: 11 November 2019
• DOI: https://doi.org/10.1108/IJOES-02-2019-0036
• Pages: 485-503
• Author: Mrinalini Srivastava,Gagan Deep Sharma,Achal Kumar Srivastava
• Subject Matter: Economics,Social economics

Human brain and f‌inancial behavior:

aneurof‌inance perspective

Mrinalini Srivastava and Gagan Deep Sharma

University School of Management Studies,

Guru Gobind Singh Indraprastha University, New Delhi, India, and

Achal Kumar Srivastava

Department of Neurology, All India Institute of Medical Sciences, New Delhi, India

Abstract

Purpose –This study aims to review the relationship between neurological processes and f‌inancial

behavior from an interdisciplinary perspective. Individual decision-making is inf‌luenced by cognitive and

affective biases; hence, it becomes pertinent to understand the origin of these biases. Neurof‌inance is an

emerging f‌ield of f‌inance budding fromneuroeconomics and explains the relationship between human brain

activity and f‌inancial behavior, drawn from interdisciplinary f‌ields, including neurology, psychology and

f‌inance.

Design/methodology/approach –This conceptual paper extensivelyreviews the extant literature and

performsmeta-analysis to attain its research objectives.

Findings –The paper highlights the use of neuroimagingtechniques in mapping the brain areas to help

understand the processes in the higher cognitive areas of brain. The paper raises some new questions

regardingindividual preferences and choices while making f‌inancialor non-f‌inancial decisions.

Originality/value –The special focus on dysfunctionsarising in brain because of injury and their impact

on decision-making is also a key pointin this paper and is summarized using meta-analytic forest plot. The

existingliterature provides instances where emotionalprocessing is altered by injury in brain and may lead to

more advantageousdecisions, especially in risky situations.

Keywords Decision-making, Neuroeconomics

Paper type Literature review

1. Introduction

The intersection of disciplines such as psychology and neurology with economics and

f‌inance is providing new guidance about f‌inancial market behavior, in recent times.

Indeed, investor behavior def‌ines asset prices using demand and supply and therefore

def‌ines f‌inancial market behavior (Ahmad et al., 2017). In particular, economists have still

not fully agreed that human behavior is “unstable”(Shiller, 1999). Hence, two schools of

thought, namely, rationalists and behaviorists, pose different theoretical approaches.

Meanwhile, the rationalist underlying premise is that human beings can evaluate weight

of probabilities of the future outcomes and consequently follow the prescription of utility

maximization. Guided by this theoretical assumption on human behavior, human beings

behave in a rational way (or full rationality) (Neumann and Morgenstern, 1953;Sapra and

Zak, 2008). The past decade, however, has shown the second school of behaviorists and

provided an alternative theoretical perspective on f‌inancial markets and assumed

irrationality or bounded rationality of human beings (investors) (Ahmad et al., 2017;

Kahneman and Tversky, 1979;Tseng, 2006). Ultimately, bounded rationality of human

beings does not mean irrationality of humans (Tseng, 2006) but rather explains how

human beings make their decisions basedontheactionsofothers(Sapra and Zak, 2008).

Human brain

and f‌inancial

behavior

485

Received10 February 2019

Revised26 February 2019

Accepted15 April 2019

InternationalJournal of Ethics and

Systems

Vol.35 No. 4, 2019

pp. 485-503

© Emerald Publishing Limited

2514-9369

DOI 10.1108/IJOES-02-2019-0036

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/2514-9369.htm

Importantly, Zehndorfer (2018) highlighted that individuals tend to react emotionally

(not rationally) when individuals deal with a stressful environment.

Human behavior is also studied by understanding the phylogeny of Homo sapiens. The

evolutionary history of Homo sapiens submits to lay the foundations of codes and

convictions of human behavior during decision-making, which is an important facet of

bioeconomics (Vromen,2007). According to Brown (2000,p.4):

[...] Biological processes are, by def‌inition, dynamic. The values taken by variables in the process

(es) and even the parameters describing variables’interaction may change over time, often

interactively. Outcomes are not entirely predictable, especially if variables interact in non-linear

ways not readily captured by static input-output coef‌f‌icients. A truly integrated bio-economic

model must capture the dynamic nature of the biological processes involved and allow for

dynamic feedback ef‌fects between human decisions, biological processes, and the range of

possibilities available for future decisions [...].

Therefore, the underlying biological processes are to be considered for the decision-

making within the economic realm. Decision-making process takes place in brain, and

thus it becomes pertinent to develop an understanding of the neural processes

responsible for decision-making. Srivastava and Sharma (2017) explain that different

aspects of human behavior are related to specif‌ic brain structures. The integration of

neural processes and economic decision-making has led to the emergence of the f‌ield of

neuroeconomics. Furthermore, Sapra and Zak (2008) in their study titled “Neurof‌inance:

bridging psychology, neurology, and investor behavior”explain the emergence of

neurof‌inance as a sub-f‌ield of neuroeconomics. Vasile and Sebastian (2010, p. 724)

maintain :

[...] Neurof‌inance is a new science that analyzes f‌inancial markets by applying neurotechnology

to trading behaviors [...].

Though neuroeconomics is considered an extension naturally coming out of bioeconomics

(Hirshleifer and Zak, 2004;Zak, 2004), it may be deduced from above that neurof‌inance

entails its extension from bioeconomics. Bioeconomics is based on the premisesof standard

economic theory’s constrained maximization framework for determining human behavior

responsible for decision-making.However, neuroeconomics and neurof‌inance do not rely on

standard economics theory for explaining the f‌inancial decision-making behavior (Vromen,

2007).

Hence, researchers of behaviorist approach seek to pay attention to explain f‌inancial

decisions of investors comprehensively: why and how particular behaviors occur (Kalra

Sahi, 2012;Tseng, 2006). Importantly, the context of decision-making matters is essential.

Despite that, the majority of previous work that explores investor behavior has used f‌ield

data or data from laboratory experiments (Frydman et al., 2014). However, such behavioral

data of investors are not enough to explain their behavior in depth. Decision-making in

f‌inance can also be referred to as problem of “socio-scientif‌ic”[1] origin as it deals with the

choice of preferences in a dynamic environment, uncertain behavior and intricate decisions

(Choudhury and Ahmed, 2013).

Despite the limited explanation of f‌inancial decision-making by investors, neuroscience

provides knowledge about the actual processes of the human brain and thus, for many

researchers, is assumedas the Holy Grail (Birnberg and Ganguly,2012). Hence, neuroscience

offers an additional kind of data, namely, neural data that can explain investors’behavior

(Frydman et al., 2014). More specif‌ically, particular brain structures are responsible for

different aspects of human behavior. Therefore, the integration of neuroscience for

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