Behavioral Finance
A Theoretical Analysis of Foundations and Models
DOI :
https://doi.org/10.23882/emss26310Mots-clés :
Behavioral Finance, Prospect Theory, Cognitive Biases, Bounded Rationality, cognitive biases, market anomalies, classical financeRésumé
This article examines the theoretical foundations of behavioural finance and analyses its relationship with classical financial theory, with the aim of clarifying whether it constitutes an autonomous paradigm or a complementary corrective framework to the rational-agent model.
Drawing on a narrative literature review of seminal contributions in behavioural economics and finance, the article critically examines five core theoretical pillars: prospect theory, mental accounting, overconfidence, herd behaviour, and heuristics. These frameworks were selected on the basis of three criteria: their extensive empirical validation, their comprehensive coverage of cognitive and emotional biases affecting investor decisions, and their direct practical relevance. They are systematically compared with the assumptions of standard finance across seven analytical dimensions synthesised in a comparative table.
The analysis shows that behavioural finance offers a robust explanatory framework for persistent market anomalies — excessive volatility, speculative bubbles, disposition effects — that classical models cannot adequately account for. Rather than constituting a complete theoretical replacement, behavioural finance represents a theoretically grounded extension of the rational-agent framework, introducing psychological realism without abandoning formal rigour. The comparative analysis reveals fundamental divergences in agent model, decision-making process, market functioning, arbitrage conception, and methodological orientation.
Behavioural finance has matured into a second-generation discipline integrating social, cultural and neuro-cognitive dimensions. Its complementarity with classical finance opens productive avenues for interdisciplinary research, with direct implications for portfolio management, financial advice, and market regulation. Future research perspectives include neurofinance, digital behavioural finance, and the integration of climate-related biases into investment decision models.
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