Publication Date: 2024/02/27
Abstract: The realm of investment is not merely a terrain of rational analysis and logical deductions; rather, it's a complex interplay of psychological biases that often steer investor decision-making processes. This abstract delves into the intricate web of behavioral biases that permeate the investment landscape, shedding light on their profound impact on investor behavior and market dynamics. Drawing from a diverse array of behavioral economics literature and empirical studies, this abstract synthesizes the prevalent biases that plague investor decision-making, ranging from overconfidence and confirmation bias to loss aversion and herd mentality. It elucidates how these biases manifest in various stages of the investment process, influencing asset allocation, portfolio diversification, and risk management strategies. Moreover, the implications of behavioral biases on market efficiency and asset pricing, highlighting the divergence between rational expectations and actual market outcomes. By dissecting the underlying mechanisms of these biases and their consequences, it underscores the importance of recognizing and mitigating their effects for both individual investors and financial institutions. It also discusses the potential synergies between traditional finance theories and behavioral economics, proposing integrated approaches that harness the strengths of both disciplines to enhance investor decision-making.At the end this topic gives us a holistic understanding of behavioral biases in the investment domain, emphasizing the need for investor education, regulatory measures, and technological innovations to foster more rational and informed decision-making processes. By unraveling the intricate interplay between psychology and finance, these abstract paves the way for a more nuanced comprehension of investor behavior and its ramifications on market dynamics.
Keywords: Behavioral Finance, Investment Decision, Availability, Regret Aversion, Representativeness, Anchoring.
DOI: https://doi.org/10.5281/zenodo.10715718
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24FEB991.pdf
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