When Numbers Compete with Nerves: Emotional Reactivity and the Breakdown of Rational Investment Behavior
DOI:
https://doi.org/10.63056/academia.5.3(s6).2026.2032Keywords:
Cognitive biases, Emotional reactivity, fintech literacy, Investment behavior, Risk aversion, Structural equation modellingAbstract
Background – Investment decisions are complex processes influenced not only by rational calculations but also by cognitive shortcuts, emotional responses, fintech literacy, and individual risk preferences. This study investigated the influence of emotional reactivity on rational investment behavior among individual investors, examining how affective biases disrupt analytical decision-making.
Objectives – Drawing on behavioral finance theory, the research aimed to understand the mechanisms through which emotions interfere with rational evaluation and risk assessment in investment contexts.
Methodology – Quantitative research design was employed, and data was collected using structured questionnaires from 390 investors with varying levels of experience, education, and demographic backgrounds. Statistical analyses, including descriptive statistics, correlation, reliability testing, ANOVA, and structural equation modeling (SEM), were conducted to examine relationships between emotional reactivity and investment behavior.
Expected Results – Results indicated a significant negative correlation, demonstrating that higher emotional reactivity was associated with reduced rational decision-making, increased risk aversion, and suboptimal portfolio strategies. Demographic variables, particularly age and investment experience, were found to moderate these effects, with younger and less experienced investors exhibiting greater susceptibility to emotional influence. The findings underscore the importance of emotional awareness, fintech literacy, and behavioral interventions in promoting rational investment practices. Implications for investors, financial institutions, and policymakers are discussed, highlighting the need for educational programs, decision-support tools, and AI-driven advisory systems to mitigate emotional biases.
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Copyright (c) 2026 Muhammad Abdul Rehman, Mumtaz Ahmad (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.







