Do Personality and Demographic Variances of Individual Investors Challenge the Assumption of Rationality? A Two-Staged Regression Modeling-Artificial Neural Network Approach

Q2 Economics, Econometrics and Finance
Arfat Manzoor, Andleebah Jan, Mohammad Shafi
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Abstract

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.
个人投资者的个性和人口差异是否挑战了理性假设?一种两阶段回归建模-人工神经网络方法
目的:本研究旨在确定人格特征和人口特征对印度北部个人投资者投资行为的影响。设计/方法/方法:本研究采用调查法和有目的的抽样技术,使用谷歌表格收集315名受访者的数据。在分析中,采用了两阶段分析法。第一阶段采用回归分析进行假设检验,第二阶段采用人工神经网络(ANN)方法对回归结果进行验证。结果发现:神经质特质对短期投资决策的影响显著为正,对长期投资决策的影响显著为负。研究发现,责任心对长期投资决策具有显著的正向预测作用,对短期投资决策具有不显著的预测作用。在人口统计变量中,教育是唯一对短期投资决策产生积极和显著影响的变量。在确定长期投资决策时,发现所有四个人口变量的作用都不显著。实践启示:本研究在散户投资者中发现其相关性,因为本研究有助于他们在做出投资决策之前了解自己的性格类型。独创性/价值:通过讨论印度散户投资者的个性特征和人口统计学差异来确定他们的投资行为,这使得本研究新颖。另一个为本研究增加独创性和新颖性的特点是使用非线性方法(ANN)和线性方法(回归)来预测决定因素的重要性。
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来源期刊
Indian Journal of Finance
Indian Journal of Finance Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)
CiteScore
1.50
自引率
0.00%
发文量
37
期刊介绍: a source of sophisticated analysis of developments in the rapidly expanding world of finance, is a double blind peer reviewed refereed monthly journal that publishes articles on a wide variety of topics ranging from corporate to personal finance, insurance to financial economics, and derivatives. It provides a forum for exchange of ideas and techniques among academicians and practitioners and thereby, advances applied research in financial management. The journal, with its mission to promote thinking on various facets of finance, is targeted at academicians, scholars, and professionals associated with the field of finance to promote pragmatic research by disseminating the results of research in finance, accounting, financial economics, and sub - areas such as theory and analysis of fiscal markets and instruments, financial derivatives research, insurance, portfolio selection, credit and market risk, statistical and empirical financial studies based on advanced stochastic methods, financial instruments for risk management, uncertainty, and information in relation to finance.
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