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The purpose of this paper is to empirically test the association of behavioral biases like overconfidence bias and self-attribution bias, and information acquisition with individual investors decisions. This study also extends its contributions in understanding the role of information acquisition in moderating the relationship of behavioral biases with investors decisions. SmartPLS 3.0 is used to analyze the structural equation model which is applied on the cross-sectional data collected from 390 individual investors of Pakistan Stock Exchange using cluster sampling technique. Findings of this study confirm that behavioral biases (overconfidence bias and self-attribution bias) distort the rationality of individual investors’ decision, and information acquisition significantly moderates the relationship of overconfidence bias with investor decisions. This study contributes to the existing behavioral finance literature by unleashing less attended potential of information acquisition in managing irrationality caused by overconfidence bias. Individual investors can use this study to better understand the adverse impact of behavioral biases as well as the usefulness of information acquisition in handling the irrationality resulted from overconfidence bias. The fruits of this study can be extended to the policy makers so that they can better steer their policies concerning the provision of information to the individual investors. Authors attempt to combine the literature of behavioral finance and information acquisition with a notion to extend new theoretical understandings relating to investor decisions.
Hasniza Mohd Taib (Corresponding author), Farrukh Naveed. (2021) Overconfidence Bias, Self-attribution Bias and Investor Decisions: Moderating Role of Information Acquisition, Pakistan Journal of Commerce and Social Sciences, Volume 15, Issue 2.
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