Study of Loss Aversion Theory Based on Connected Papers AI - Rahmah Dianti Putri; Mahatma Kufepaksi; Prakarsa Panjinegara (Journal of International Conference Proceedings, 2025)
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.