Beyond the hype: AI advice and investor dissonance in crypto trading

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F25%3A63589579" target="_blank" >RIV/70883521:28120/25:63589579 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s12144-025-07430-w" target="_blank" >https://link.springer.com/article/10.1007/s12144-025-07430-w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s12144-025-07430-w" target="_blank" >10.1007/s12144-025-07430-w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Beyond the hype: AI advice and investor dissonance in crypto trading

Popis výsledku v původním jazyce

This study examines the impact of cognitive dissonance on the relationship between investors&apos; intentions to use AI advice and their investment behaviour in the cryptocurrency market. The study recruited 348 individuals through a non-random snow-ball sampling technique. Utilising ChatGPT for investment recommendations, the research involves a trading experiment accompanied by a two-stage survey to evaluate investor attitudes towards AI before and their cognitive dissonance levels after the experiment. Structural Equation Modelling (SEM) identifies the connection between the intent to use AI and the influence of cognitive dissonance on investment decisions. Results indicate that investors following AI advice outperformed those who did not, attributable not to AI&apos;s predictive power but to reduced cognitive dissonance. This reduction allowed investors using AI to cut losses more effectively, in contrast to those who eschewed AI advice and tended to hold onto losing positions longer, leading to worse performance. Although focused on the cryptocurrency market, the findings suggest a potential for broader applicability in conventional financial markets. The study&apos;s key contribution is demonstrating that AI recommendations can mitigate the disposition effect, implying that AI&apos;s broader implementation could enhance market efficiency.

Název v anglickém jazyce

Beyond the hype: AI advice and investor dissonance in crypto trading

Popis výsledku anglicky

This study examines the impact of cognitive dissonance on the relationship between investors&apos; intentions to use AI advice and their investment behaviour in the cryptocurrency market. The study recruited 348 individuals through a non-random snow-ball sampling technique. Utilising ChatGPT for investment recommendations, the research involves a trading experiment accompanied by a two-stage survey to evaluate investor attitudes towards AI before and their cognitive dissonance levels after the experiment. Structural Equation Modelling (SEM) identifies the connection between the intent to use AI and the influence of cognitive dissonance on investment decisions. Results indicate that investors following AI advice outperformed those who did not, attributable not to AI&apos;s predictive power but to reduced cognitive dissonance. This reduction allowed investors using AI to cut losses more effectively, in contrast to those who eschewed AI advice and tended to hold onto losing positions longer, leading to worse performance. Although focused on the cryptocurrency market, the findings suggest a potential for broader applicability in conventional financial markets. The study&apos;s key contribution is demonstrating that AI recommendations can mitigate the disposition effect, implying that AI&apos;s broader implementation could enhance market efficiency.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50103 - Cognitive sciences

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Current Psychology

ISSN

1046-1310

e-ISSN

1936-4733

Svazek periodika

44

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

3313-3325

Kód UT WoS článku

001404832400001

EID výsledku v databázi Scopus

2-s2.0-105003748049