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All Journal Journal of Indonesian Economy and Business Journal of International Conference Proceedings
Mahatma Kufepaksi
University of Lampung
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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DO OVERCONFIDENT INVESTORS TRADE EXCESSIVELY IN THE CAPITAL MARKET? EVIDENCES IN AN EXPERIMENTAL RESEARCH SETTING Mahatma Kufepaksi
Journal of Indonesian Economy and Business (JIEB) Vol 26, No 2 (2011): May
Publisher : Faculty of Economics and Business, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (136.961 KB) | DOI: 10.22146/jieb.6271

Abstract

The existence of overconfident investors in capital markets has been the subject of much researches in the past. Using the market data, these previous researches demonstrates that overconfident investors tend to trade excessively, leading to losses. The current experimental research addresses these issues in the Indonesia Capital Market. According to its methodology, participants are classified into three groups based on their score of overconfidence: moderate, more overconfident, and less overconfident investors. The research design employs the state of no available market information, good news signals, and bad news signals as treatments. The result demonstrates that the more overconfident investors perform higher trading value than those who are less overconfident in all artificialmarkets leading to transaction losses, except that in the bad news market. In that bad news market, the more and the less overconfident investors gain profits, and the moderateinvestors suffer from trading losses.Keywords: overconfidence, excessive trading, profit and loss
Study of Loss Aversion Theory Based on Connected Papers AI Rahmah Dianti Putri; Mahatma Kufepaksi; Prakarsa Panjinegara
Journal of International Conference Proceedings Vol 8, No 7 (2025): 2025 Bali ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v8i7.4723

Abstract

This study aims to analyze loss aversion behavioral bias in the capital market by utilizing artificial intelligence technology. The method used in this study is a literature review, and the literature sources were obtained using Connected Papers AI by entering the keyword “Loss Aversion.” Next, several recommended article titles related to the keyword will appear. In this study, the author chose the article title “Behavioral Risk Profiling: Measuring Loss Aversion of Individual Investors” as the main article. Then, Connected Papers AI created a visualization graph of articles that have a strong relationship with the reference article in terms of co-citation and bibliography merging. The author used the articles based on the visualization graph to create a literature review. From the visualization results, it can be seen that research on loss aversion is rooted in decision-making theory under risk, based on the prospect theory framework. aversion in time frame or social conditions.
Co-Authors Prakarsa Panjinegara Rahmah Dianti Putri