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Guest editorial: Special issue: Applications of artificial intelligence and machine learning in business, finance and economics

2024; Emerald Publishing Limited; Volume: 31; Issue: 2 Linguagem: Inglês

10.1108/rege-04-2024-209

2177-8736

Leandro Maciel, Plamen Angelov, Fernando Gomide,

Forecasting Techniques and Applications

Artificial intelligence (AI) is the simulation of intelligence by machines.Machine learning (ML) is a branch of AI that focuses on the use of data by algorithms to learn and extract valuable information that enables problem-solving and decision-making.In the contemporary landscape of business, finance and economics, the integration of AI and ML technologies has emerged as a pivotal force driving innovation, efficiency and strategic decision-making.For instance, the intersection of AI and ML with business operations is reshaping traditional paradigms across various sectors.From streamlining processes and enhancing customer experiences, to optimizing supply chains and predicting market trends, the deployment of intelligent algorithms is revolutionizing how organizations operate and even the way we interpret market dynamics.In the realm of finance, AI and ML are catalyzing significant advancements in risk management, portfolio optimization and algorithmic trading.These technologies enable financial institutions to assess creditworthiness, detect fraudulent activities and automate routine tasks with heightened accuracy and efficiency.In economics, AI and ML methodologies are unlocking new frontiers in research, policy formulation and market analysis.Researchers leverage these tools to analyze complex economic phenomena, forecast macroeconomic indicators and simulate policy interventions with unprecedented granularity and accuracy.The continued advancement of AI and ML technologies holds immense promise for reshaping the future landscape of business, finance and economics.This special issue (SI) aims to present the latest developments and innovative ways to use data analysis and learning methods for practical decisions and analyses in managerial tasks.The key objective is to provide a forum to stimulate the continuing effort in the application of AI and ML approaches to solve problems in business, finance and management.The SI has attracted 23 papers covering distinct applications of AI and ML.After rounds of reviews by national and international experts, seven papers were selected for this special issue.We briefly summarize these curated papers below.The work "Market efficiency assessment for multiple exchanges of cryptocurrencies" by Souza and Carvalho (2024) analyzes the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms.The EMH was evaluated in a multivariate way using a traditional econometric modeling framework: vector autoregression.The findings gave evidence of Granger causality between cryptocurrencies on all exchanges.