The Effect of Overconfidence Bias on Investment Decision: Sharia Stock Considerations

Wahyu Febri Ramadhan Sudirman; Nurnasrina Nurnasrina; Muhammad  Syaipudin; Arif Mudi Priyatno

doi:10.31004/jutin.v7i2.26091

Authors

Wahyu Febri Ramadhan Sudirman Univeristas Pahlawan Tuanku Tambusai https://orcid.org/0000-0002-9562-7732
Nurnasrina Nurnasrina Universitas Islam Negeri Sultan Syarif Kasim Riau
Muhammad Syaipudin Universitas Pahlawan Tuanku Tambusai
Arif Mudi Priyatno Universitas Pahlawan Tuanku Tambusai

DOI:

https://doi.org/10.31004/jutin.v7i2.26091

Keywords:

over-estimate, over-precision, over-placement, overconfidence, investment decision

Abstract

Investment decisions are a complex process involving risk evaluation, market analysis, and investment return projections. In the decision-making process, investors sometimes show irrational behavior because they have cognitive limitations and previous investment experience so investors are exposed to overconfident behavior. This research used 178 samples consisting of investors who had investment experience of at least 1 year. The research carried out instrument testing and used the common method bias (CMB) testing procedure. The analytical method in the research uses simple linear regression. The results of testing the research hypothesis obtained positive and significant results of overconfidence bias towards irrational investment decisions The moderating role of sharia sharia considerations on the relationship between overconfidence bias and unsupported investment decisions. This research reveals that overconfidence can have a positive influence on irrational investment decision-making. Investors who tend to have excess confidence in their knowledge and skills in analyzing the market tend to make investment decisions that are more impulsive, less rational and sometimes ignore risks significantly. Future research is recommended to further investigate the mechanisms behind the relationship between overconfidence and irrational investment decision-making, as well as involving a wider sample to obtain stronger generalizations.

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