Analyzing the Robust Factors of Overconfidence Bias and its Impact:An Interpretive Structural Modeling Approach
Keywords:
Behavioral Traits
, Hierarchical Structure (Drivers, Enablers, and Dependent Variables), Interpretive Structural ModelingC6
, G00, G02Paper Submission Date
, May 16, 2015, Paper sent back for Revision, June 5, Paper Acceptance Date, September 5, 2015.Abstract
People have a tendency to have too much reliance on the accuracy of their own judgments. This inclination boosts up the confidence limit of an individual, as people have the propensity to compare quantity with quality. Overconfidence is one of the prominent behavioral traits, which persuade an individual to make poor investment decisions without doing an impartial analysis of the available options. The distortion in the investment decision-making process is led by overconfident behavior which itself is adversely affected by a few of the factors. The objective of this paper was to explore and develop the relationships among the reviewed variables by keeping at the center the psychology of stock market investors. The interpretive structural modeling (ISM) methodology was used for identifying the prominent factors in a sequential manner. This provided a hierarchical structure apprenticing with planning, execution, categorizing, and conclusion, by way of providing output for the whole process. The factors were categorized as drivers, enablers, and dependent variables in the hierarchy of the ISM model. This model provided a framework for investors to spot out the robust factors of overconfidence in an orderly manner in the stock market, which distorts the investment decision making process.Downloads
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