Artificial intelligence in digital finance and cryptomarkets: challenges and opportunities

• Grant number: 22/01524-2
• Support Opportunities: Regular Research Grants
• Start date: July 01, 2022
• End date: December 31, 2024
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Paulo Andre Lima de Castro
• Grantee: Paulo Andre Lima de Castro
• Host Institution: Divisão de Ciência da Computação (IEC). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil

Abstract

Artificial Intelligence (AI) and its related fields such as machine learning and Robotics are changing the world, as we know it. It is also true for the financial field. Furthermore, the progress of digitization in finance has created new markets, specially the so called cryptomarkets, which includes Bitcoin, Ethereum and many other cryptoassets, which are characterized by high volatility and different views about their viability and methods of valuation. These features and breakthroughs in AI, such as deep learning, bring opportunities for innovation and research. However, there are also many pitfalls in financial environments, which are often misunderstood or simply unknown to many AI practitioners and researchers addressing it. Financial problems may be much harder than recognizing faces or driving cars, because patterns often evolve as time goes by and which information is relevant may change with the financial assets. In this initiative, we intend to (1) clarify and describe the financial environment for AI researchers and practitioners including the several pitfalls (2) develop conceptual and methodological procedures in order to tackle these problems in both traditional and cryptomarkets (3) identify or create tools to support the application of the defined procedures. This project benefits from recent and relevant work published in the intersection of Economics and Computation. In fact, ACM created a special interest group to encourage research at the interface between economics and computation, including Finance, Artificial Intelligence and many other fields. Initiatives as this one can benefit both areas and may have impact in practical applications not just, as AI based solution to financial problems, but it may also contribute to development or improvement of new AI algorithms (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SBRANA, ATTILIO; BIZARRO MIRISOLA, LUIZ GUSTAVO; SOMA, NEI YOSHIHIRO; LIMA DE CASTRO, PAULO ANDRE. Solving NP-Complete Akari games with deep learning. ENTERTAINMENT COMPUTING, v. 47, p. 8-pg., 2023-05-29. (22/01524-2)

SBRANA, ATTILIO; DE CASTRO, PAULO ANDRE LIMA. N-BEATS Perceiver: A Novel Approach for Robust Cryptocurrency Portfolio Forecasting. COMPUTATIONAL ECONOMICS, v. N/A, p. 35-pg., 2023-09-22. (22/01524-2)