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ZENODO
Journal . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
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EMPIRICAL STUDY ON THE ROLE OF ARTIFICIAL INTELLIGENCE IN MITIGATING BEHAVIOURAL BIASES AMONG INDIAN RETAIL INVESTORS

Authors: Asst. Prof. Nihar Manoj Shanischara;

EMPIRICAL STUDY ON THE ROLE OF ARTIFICIAL INTELLIGENCE IN MITIGATING BEHAVIOURAL BIASES AMONG INDIAN RETAIL INVESTORS

Abstract

Democratization of the Indian equity market has spurred considerable growth in retail investor participation; however, the vast majority of retail investors do not outperform the benchmark Nifty 50 index. Most of these retail investors underperform relative to their benchmark due to irrational decision-making habits (i.e., psychological heuristics). The purpose of this study was to collect primary data from 75 Indian retail investors in order to assess the extent to which these individuals experience fear, greed, and herd mentality in their decision-making processes. The results of this study indicate that panic selling (Mean = 3.89) and herd impact (Mean = 3.84) are most prevalent among Indian retail investors in addition to a large awareness-action gap. In addition to fear, greed, and herd mentality, we also evaluated various artificial intelligence (AI) based tools that are currently available to the retail investor; specifically, we evaluated the effectiveness of automated rebalancing (Mean = 4.21) and risk alerts (Mean = 4.17) as effective rational circuit breakers. We were able to conclude that while human emotion is an integral part of the decision-making process, the use of AI allows retail investors to maintain discipline while investing during times of market volatility.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green