Do Personality and Demographic Variances of Individual Investors Challenge the Assumption of Rationality? A Two-Staged Regression Modeling-Artificial Neural Network Approach
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Purpose: The present study aimed to determine the influence of personality traits and demographic characteristics on the investment behavior of individual investors in North India.
Design/Methodology/Approach: The current study adopted a survey method and purposive sampling technique to collect the data from 315 respondents using Google Forms. For analysis, a two-stage analysis approach was adopted. In the first stage, regression analysis was used for hypotheses testing, and in the second stage, an artificial neural network (ANN) approach was adopted to validate the regression results.
Findings: The impact of the neurotic trait was found to be significantly positive on short-term investment decisions and significantly negative on long-term investment decisions. Conscientiousness was found to be a positive and significant predictor of long-term investment decisions and an insignificant predictor of short-term investment decisions. Among demographical variables, education was the only variable that positively and significantly impacted short-term investment decisions. In determining the long-term investment decisions, the role of all four demographic variables was found to be insignificant.
Practical Implications: This study found its relevance among retail investors as this study would assist them in knowing their personality type before making investment decisions.
Originality/Value: Determining the investment behavior of Indian retail investors by debating their personality traits and demographic variances made this study novel. The other feature that adds originality and novelty to this study is the use of a non-linear approach (ANN) along with a linear approach (regression) to predict the significance of the determining factors.
Keywords
neuroticism, conscientiousness, demography, investment decisions, regression, ANN
JEL Classification Codes : G1, G2, G4, G5
Paper Submission Date : September 30, 2022 ; Paper sent back for Revision : May 5, 2023 ; Paper Acceptance Date : July 25, 2023 ; Paper Published Online : October 15, 2023
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