Behavioral Biases Influencing Individual Investors Decision Making in Bearish Trend at Nepse

Pandey Anshu
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Abstract

The discipline of financial economics has seen a paradigm shift over the past 25 years, moving from traditional finance to a new area of the study known as behavioral finance. Due to a multitude of behavioral biases and emotional attachments, professional investors make bad financial decisions that hinder their investing performance. Due to the increase in individual investors over the past several years, which is predicted to continue in the years to come, the problem of behavioral biases may become more and more important. Overconfidence bias, representativeness bias, disposition bias, loss aversion bias, herding bias and market factors are the independent variables, whereas investment decision making is the dependent variable. Questionnaires were used to collect primary data. 200investors were sampled using the convenience sampling technique, and data obtained was subjected to regression analysis. The SPSS was used to analyze data collected in order to generate descriptive statistics for the study. The extent to which the dependent variables could be explained by the independent variable was described using regression analysis. The study thus suggests that individual investors be educated how to avoid poor investment outcomes caused on by behavioral biases. Furthermore, individual investors should seek the advice of stock brokers/fund managers to guide them accordingly in terms of performance of a specific security in which an investor would wish to invest in.
影响个人投资者的行为偏差Nepse看跌趋势中的决策制定
在过去的 25 年里,金融经济学的研究范式发生了转变,从传统金融学转向了一个新的研究领域,即行为金融学。由于多种行为偏差和情感依附,专业投资者会做出错误的金融决策,从而影响他们的投资业绩。由于过去几年个人投资者的增加,而且预计在未来几年还会继续增加,行为偏差问题可能会变得越来越重要。过度自信偏差、代表性偏差、处置偏差、损失规避偏差、羊群偏差和市场因素是自变量,而投资决策是因变量。调查问卷用于收集原始数据。使用便利抽样技术抽取了 200 名投资者,并对获得的数据进行了回归分析。使用 SPSS 对收集到的数据进行分析,以生成研究的描述性统计数据。使用回归分析描述了自变量对因变量的解释程度。因此,研究建议教育个人投资者如何避免行为偏差造成的不良投资结果。此外,个人投资者应征求股票经纪人/基金经理的意见,以便在投资者希望投资的特定证券的表现方面为他们提供相应的指导。
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