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JMI - Journal of Management and Informatics - Vol. 3 Issue. 3 (2024)

Behavioral Biases in Investment Decisions: A Mixed-Methods Study on Retail Investors in Emerging Markets

Ahmad Ashifuddin Aqham, Eny Endaryati, Vivi Kumalasari Subroto, Robby Andika Kusumajaya,



Abstract

Retail investment in emerging markets has experienced rapid growth, driven by technological advancements and increasing public awareness of financial management. However, behavioral biases often influence retail investment decision-making, such as overconfidence and herding, which can undermine portfolio performance. This study aims to identify the key behavioral biases affecting retail investors' decision-making in emerging markets and analyze their impact on investment performance. A mixed-methods approach was employed, combining a quantitative survey of 200 retail investors with in-depth interviews to gain qualitative insights. The results reveal that overconfidence bias dominates, with a prevalence of 70%, followed by herding bias at 50%, anchoring at 40%, and loss aversion at 60%. Overconfidence bias showed a significant positive correlation with investment returns (r = 0.65, p < 0.01), while herding (r = -0.48, p < 0.03), anchoring (r = -0.35, p < 0.05), and loss aversion (r = -0.60, p < 0.02) had negative impacts on portfolio performance. This research contributes to the behavioral finance literature by highlighting the unique conditions of emerging markets, such as low financial literacy and limited access to information, which exacerbate the effects of behavioral biases. As a practical implication, the development of behavioral finance-based educational programs is recommended to help investors understand and manage these biases. Furthermore, future research is encouraged to explore the use of alternative data, such as social media, to monitor behavioral trends in real-time







Publisher :

Universitas Sains dan Teknologi Komputer

DOI :


Sitasi :

0

PISSN :

2961-7731

EISSN :

2961-7472

Date.Create Crossref:

27-Jan-2025

Date.Issue :

30-Dec-2024

Date.Publish :

30-Dec-2024

Date.PublishOnline :

30-Dec-2024



PDF File :

Resource :

Open

License :

https://creativecommons.org/licenses/by-sa/4.0