To read this content please select one of the options below:

The role of artificial intelligence in the decision-making process: a study on the financial analysis and movement forecasting of the world’s largest stock exchanges

Ewerton Alex Avelar (Accounting and Finance Department, UFMG, Belo Horizonte, Brazil)
Ricardo Vinícius Dias Jordão (The Center for Advanced Studies in Management and Economics, CEFAGE-UE, Evora, Portugal) (Swiss Management Center, Zug, Switzerland) (Graduate Program in Business Administration, FPL, Pedro Leopoldo, Brazil)

Management Decision

ISSN: 0025-1747

Article publication date: 5 July 2024

480

Abstract

Purpose

This paper aims to analyze the role and performance of different artificial intelligence (AI) algorithms in forecasting future movements in the main indices of the world’s largest stock exchanges.

Design/methodology/approach

Drawing on finance-based theory, an empirical and experimental study was carried out using four AI-based models. The investigation comprised training, testing and analysis of model performance using accuracy metrics and F1-Score on data from 34 indices, using 9 technical indicators, descriptive statistics, Shapiro–Wilk, Student’s t and Mann–Whitney and Spearman correlation coefficient tests.

Findings

All AI-based models performed better than the markets' return expectations, thereby supporting financial, strategic and organizational decisions. The number of days used to calculate the technical indicators enabled the development of models with better performance. Those based on the random forest algorithm present better results than other AI algorithms, regardless of the performance metric adopted.

Research limitations/implications

The study expands knowledge on the topic and provides robust evidence on the role of AI in financial analysis and decision-making, as well as in predicting the movements of the largest stock exchanges in the world. This brings theoretical, strategic and managerial contributions, enabling the discussion of efficient market hypothesis (EMH) in a complex economic reality – in which the use of automation and application of AI has been expanded, opening new avenues of future investigation and the extensive use of technical analysis as support for decisions and machine learning.

Practical implications

The AI algorithms' flexibility to determine their parameters and the window for measuring and estimating technical indicators provide contextually adjusted models that can entail the best possible performance. This expands the informational and decision-making capacity of investors, managers, controllers, market analysts and other economic agents while emphasizing the role of AI algorithms in improving resource allocation in the financial and capital markets.

Originality/value

The originality and value of the research come from the methodology and systematic testing of the EMH through the main indices of the world’s largest stock exchanges – something still unprecedented despite being widely expected by scholars and the market.

Keywords

Acknowledgements

We are very grateful for the comments and suggestions for improvement from reviewers and editors during the editorial process. They have helped us to perfect the manuscript significantly and improve its quality and rigor.

Funding: The authors are pleased to acknowledge the financial support from Minas Gerais State Agency for Research and Development – FAPEMIG (No. APQ-01497-21) and the National Funds of the FCT - Portuguese Foundation for Science and Technology (No. UID / ECO / 04007/2021).

Citation

Alex Avelar, E. and Jordão, R.V.D. (2024), "The role of artificial intelligence in the decision-making process: a study on the financial analysis and movement forecasting of the world’s largest stock exchanges", Management Decision, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MD-09-2023-1625

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

Related articles