Published Online:July 2025
Product Name:The IUP Journal of Accounting Research & Audit Practices
Product Type:Article
Product Code:IJARAP260725
DOI:10.71329/IUPJARAP/2025.24.3.562-580
Author Name:Saidalavi, Rasheed K and Afeefa Cholasseri
Availability:YES
Subject/Domain:Finance
Download Format:PDF
Pages:562-580
The paper examines the impact of artificial intelligence (AI) trading tools on three major cognitive biases: loss aversion, overconfidence bias and anchoring bias. Primary data was collected from 400 traders in India who use AI trading platforms like algorithmic trading systems, robo-advisors, sentiment analysis models, and predictive analytics platforms. A structured questionnaire was administered to assess the effect of AI trading tools on cognitive biases. Loss aversion was measured based on items from Kahneman and Tversky’s (1979) prospect theory; overconfidence bias was evaluated based on Glaser et al. (2013) investment decision-making scale; and anchoring bias was measured using Tversky and Kahneman’s (1974) anchoring bias framework. AI trading tool usage was measured by a custom-designed scale to evaluate the frequency, reliance and perception of AI-based trading platforms. The findings reveal that AI trading tools reduce loss aversion, encouraging traders to take more calculated risks, while simultaneously amplifying overconfidence and anchoring biases.
The financial markets are increasingly getting integrated with artificial intelligence (AI), which has improved trading strategies through machine learning (ML) and predictive analytics. AI trading software provides insights that are backed by data, thus minimizing human error and improving investment decisions.