自动化偏见和现状偏见对印度投资者资本市场投资决策的影响:解释性研究

Shivam Shukla, Sudhir Kumar Shukla
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摘要

本研究探讨了自动化偏见和现状偏见对印度散户资本市场投资决策的存在及其影响。在行为经济学中,“自动化偏差”一词指的是投资者在选股决策中过度依赖自动或计算机生成的信息。另一方面,维持现状的偏见是投资者的内在倾向,保持其投资组合不变,而不管资本市场的动态变化出于各种原因。在本研究中,我们试图找出这两种偏见在投资者投资决策中的存在程度和影响程度。这项研究是基于通过一个五点李克特量表问卷收集的数据,该问卷旨在找出研究问题的答案。调查问卷在国家证券交易所(NSE)和孟买证券交易所(BSE)的496名散户投资者中分发。本研究的结果清楚地指出,印度资本市场投资者的投资决策中确实存在自动化偏差和现状偏差,并且这两种偏差对印度投资者的投资决策的影响程度相当大,且具有统计学意义(p<0.05)。该研究还得出结论,投资者必须采取某些措施,以避免在投资决策中出现行为偏差,并保护他们的投资组合免受不必要的、可能具有破坏性的行为错误或陷阱的影响。研究人员坚信,本研究是对散户投资者的自动化偏差和现状偏差进行研究的首次尝试,将对行为经济学研究特别是从资本市场投资者的角度分析行为偏差带来一些重要启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of Automation Bias and Status Quo Bias on Capital Market Investment Decisions of Indian Investors: An Explanatory Research
The present study explores the presence and impact of automation bias and status quo bias on the capital market investment decisions of Indian retail investors. In behavioral economics the term automation bias is known as the excessive dependency of investors on automated or computer generated information for stock selection decisions. On the other hand, status quo bias is the inherent tendency of an investor to keep his portfolio unaltered irrespective of the changing dynamics of capital market for a variety of reasons. In this study an attempt has been made to figure out the extent of presence and degree of impact of both the biases in the investment decisions of investors. The study is based on data collected through a five point Likert scale questionnaire framed to figure out answers to the research questions. The questionnaire was distributed among 496 retail investors of National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). The outcome of this study clearly point out that there is a definite presence of automation bias and status quo bias in investment decisions of the capital market investors of India and there is a considerable and statistically significant (p<0.05) magnitude of impact of both the biases on the investment decisions of Indian investors. The research also concludes that certain steps must be taken by investors to keep away from behavioral biases in investment decisions and shield their portfolio from unwarranted and potentially damaging behavioral mistakes or pitfalls. The researchers have a strong belief that this research is a maiden attempt to study automation bias and status quo bias among retail investors and will bring about some significant revelations in the study of behavioral economics particularly in the analysis of behavioral biases from the standpoint of capital market investors.
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