Behavioral Finance and its impact on Investor Decision-Making

Traditional financial theories, particularly the Efficient Market Hypothesis (EMH), rest on the premise that investors behave as rational agents, making decisions grounded purely in logic and the information at hand. In practice, financial markets frequently stray from these tidy assumptions—prompting the rise of Behavioral Finance, a field that merges economic analysis with psychological insight to clarify why investors often act irrationally. This thesis investigates how behavioral finance shapes investor decision-making, paying special attention to psychological biases and heuristics such as overconfidence, loss aversion, herd behavior, and mental accounting. The research employs a combination of literature review, real-world case studies, and original data collection through surveys and interviews, seeking to reveal patterns in investor behavior that depart from strictly rational models. The findings underscore the significant influence of behavioral factors on investment outcomes, frequently leading to less-than-optimal choices. Recognizing these biases can equip financial advisors, policymakers, and investors themselves with tools to lessen their impact, supporting better decision-making and fostering greater stability in financial markets. Ultimately, this thesis enriches the growing literature on behavioral finance, emphasizing its practical value for investment strategy, risk management, and financial education.