ChatGPT’s crystal ring: simulating auditors’ use of machine learning in stock price prediction

ABSTRACT

This study investigates the influence of technological factors on the intent to use Machine Learning (ML) tools such as Python for the purpose of predicting stock prices. Further, it investigates the moderate impact of Artificial Intelligence (AI) models usage, in particular ChatGPT, on these associations. The outcomes of a simulation involving 400 auditors, accounting for the heterogeneity of their competencies, were obtained through code utilisation based on the Python programming language. The technological factors drawn from diffusion of innovation theory (DOI), including relative advantages, Complexity, compatibility, observability, and triability, all showed positive associations with behavioural intent. The use of ChatGPT significantly fortified these connections. These results suggest a fruitful symbiotic outcome may be achieved by combining AI capabilities with these variables. The findings underscore the significance of planning for the adoption of AI in financial decision-making and auditing and also illustrate the potential of AI in these areas.

KEYWORDS:

• Python
• ChatGPT
• simulation
• stock prices
• auditor
• DOI

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. In order to guarantee the accuracy and applicability of the simulation, a panel of auditors was engaged during its development, offering firsthand accounts and perspectives to enhance the simulated data and inquiries.

2. Both structural equation modelling (SEM) and OLS were employed in our analysis, and the results of both methods are the same. However, we opted to report the OLS results as they aligned more closely with our research objectives (i.e. direct relationships). SEM is particularly appropriate when the primary focus of analysis is on both direct and indirect relationships, which is not our case. Thereby, OLS allows us to present the most uncomplicated outcomes without compromising their validity.