Exploring Biases and Personality Traits in Investment Decision: A Cluster Analysis Approach

Abstract

Much has been written about biases both in the area of behavioural economics and finance. From assuming them to be a flaw in human behaviour to shortcuts in decision-making, there is a wide range of studies available. However, a common acceptance in all these studies is that biases are present in everyone and cast their impact on real-life decision-making either knowingly or unknowingly. This study endeavours to unveil how selected biases operate along with personality traits and eventually influence investment decisions. Three prominent biases viz., overconfidence bias, representativeness bias and loss aversion bias are selected. Cluster analysis is employed to segment investors into groups based on their personality and prominent bias. Five different clusters of investors emerged which is also supplemented by ANOVA to understand the difference between these clusters. Fascinating findings were obtained highlighting the role of bias and personality in respect of investment decisions. This study is the first to unveil the combined effect of personality and bias on investment decisions and hold insights both theoretical and practical.