This literature review explores the diverse methodologies within the field of evolutionary finance, highlighting its theoretical foundations, applications, and implications for financial modeling and decision-making. Evolutionary finance, which integrates concepts from evolutionary biology, behavioral finance, and complexity theory, provides a unique perspective on market dynamics and the behavior of financial agents. This review systematically categorizes existing research into key themes, including agent-based modeling, evolutionary game theory, and adaptive markets, and assesses their contributions to understanding financial phenomena such as asset pricing, market efficiency, and risk management. By synthesizing findings from a wide range of studies, this paper identifies gaps in the literature and suggests future research directions to enhance the theoretical and practical aspects of evolutionary finance. Ultimately, this review aims to provide scholars and practitioners with a comprehensive understanding of evolutionary finance methodologies and their potential for shaping the future of financial research and practice.

Evolutionary Finance, Literature Review, Methodologies

Alwathainani, A. (2012), “Consistent winners and losers”, International Review of Economics and Finance, Vol. 21, pp. 210-220.

Arthur, B., Holland, J., LeBaron, B., Palmer, R., Tayler, P., (1997), “Asset Pricing Under Endogenous Expectations in an Artificial Stock Market”, The Economy as an Evolving Complex System II, pp. 15-44.

Baltussen, G., (2009), “Behavioral Finance: an Introduction”, SSRN Working Paper.

Barber, B. and Odean, T. (2002), “Online Investors: Do the Slow Die First”, Review of Financial Studies, Vol. 15, pp. 455-488.

Barberis, N., Shleifer, A. and Vishny, R. (1998), “A model of investor sentiment”, Journal of Financial Economics, Vol. 49, pp. 1-53.

Bernardo, A. and Welch, I. (2001), “On the Evolution of Overconfidence and Entrepreneurs”, Journal of Economics and Management Strategy, Vol. 10, pp. 301-330.

Bikhchandani, S., Hirshleifer, D. and Welch, I. (1992), “A theory of Fads, Fashion, Custom and Cultural Change as Informational Cascades”, Journal of Political Economy, Vol. 100, pp. 992-1026.

Blasco, N., Corredor, P. and Ferreruela, S. (2012), “Does Herding Affect Volatility? Implications for the Spanish Stock Market”, Quantitative Finance, Vol. 12, pp. 311-327.

Bloomfield, R. and Hales, J. (2002), “Predicting the next step of a random walk: experimental evidence of regime-shifting beliefs”, Journal of Financial Economics, Vol. 65, pp. 397-414.

Boussaidi, R. (2013), “Representativeness Heuristic, Investor Sentiment and Overreaction to Accounting Earnings: The Case of the Tunisian Stock Market”, Procedia Social and Behavioral Sciences, Vol. 81, pp. 9 -21.

Brock, W. and Hommes, C. (1998), “Heterogeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Model”, Journal of Economic Dynamics and Control, Vol. 22, pp. 1235-1274.

Campbell, J. (2000), “Asset Pricing at the Millennium”, Journal of Finance, Vol. 55, pp. 1515-1567.

Cen, L., Hilary, G. and Wei, J. (2013), “The Role of Anchoring Bias in the Equity market: Evidence from Analysts’ Earnings Forecasts and Stock Returns”, Journal of Financial and Quantitative Analysis, Vol. 48, pp. 47-76.

[Chang, E., Cheng, W. and Khorana, A. (2000), “An Examination of Herd Behavior in Equity Markets: an International Perspective”, Journal of Banking and Finance, Vol. 24, pp. 1651-1699.

Charness, G., Karni, E. and Levin, D. (2010), “On the Conjunction Fallacy in Probability Judgment: New Experimental Evidence Regarding Linda”, Games and Economic Behavior, Vol. 68, pp. 551-556.