Potential Underdog Bias, Overconfidence and Risk Propensity in Investor Decision-Making Behavior

Abstract

Investor decision-making requires an absence of bias and appropriate levels of risk-taking. In this study we investigate whether investors are prone to take risks, both in terms of how they rate their risk propensity and their behavior in choosing between options with different risk levels, and whether they display overconfidence and underdog bias. We also investigate the relationships among underdog bias, overconfidence and risk propensity. The results indicate overconfidence levels similar to that in other populations and do not reveal underdog bias or high levels of risk propensity. We found support for a negative predictive relationship between underdog bias and overconfidence. Further findings reveal that the highest self-ratings appeared for those with most investment experience, and females displayed higher underdog bias than men. The findings hold implications for the development of self-perception in investors.

Multidimensional Risk and Religiosity Towards Indonesian Muslims’ Sharia Investment Decision

“…Hamid, Rangel, Taib, and Thurasamy (2013) show that risk propensity affects risk investment decisions. However, Combrink and Lew (2019) found no significant relationship between risk propensity and decisionmaking behaviour. They found no relationship between how investors rated their successes and the propensity to take a risk or choose riskier options when faced with two choices (Combrink & Lew, 2019).…”

Over Confidence, Mental Accounting, and Loss Aversion In Investment Decision

“…9, No. 1, April, 2021 E-ISSN: 2461-0607 investment decisions and Combrink & Lew (2020) shows the results of the negative relationship overconfidence to investment decisions. Another psychology is mental accounting, which is the thought of investors who always consider the costs and benefits of decisions taken (Nofsinger & Nofsinger, 2018).…”

Why retail investors traded equity during the pandemic? An application of artificial neural networks to examine behavioral biases

“…Behavioral biases have attracted researchers' attention over the past several decades (e.g., Baker et al, 2019; Tversky & Kahneman, 1986), with different biases being proposed and examined to explain retail investors' decision‐making. In this regard, some of the recently examined behavioral biases are the disposition effect in the options market (Bergsma et al, 2019), overconfidence and underdog bias (Combrink & Lew, 2019), home bias tendency while trading (Gavish et al, 2020), and myopic loss aversion (Durand et al, 2019). While the accumulated knowledge is rich, the literature is deficient in terms of three aspects: First, there are limited prior studies on investor behavior in the face of an external stressor, such as a global health crisis, even though the existing scholarship has noted the impact of events, such as the Ebola virus outbreak (Ichev & Marinč, 2018) and various disasters (Kowalewski & Śpiewanowski, 2020) on stock market returns.…”