AI in the Financial Markets

This book is divided into two parts, the first of which describes AI as we know it today, in particular the Fintech-related applications. In turn, the second part explores AI models in financial markets: both regarding applications that are already available (e.g. the blockchain supply chain, learning through big data, understanding natural language, or the valuation of complex bonds) and more futuristic solutions (e.g. models based on artificial agents that interact by buying and selling stocks within simulated worlds).

The effects of the COVID-19 pandemic are starting to show their financial effects: more companies in a liquidity crisis; more unstable debt positions; and more loans from international institutions for states and large companies. At the same time, we are witnessing a growth of AI technologies in all fields, from the production of goods and services, to the management of socio-economic infrastructures: in medicine, communications, education, and security. The question then becomes: could we imagine integrating AI technologies into the financial markets, in order to improve their performance? And not just limited to using AI to improve performance in high-frequency trading or in the study of trends. Could we imagine AI technologies that make financial markets safer, more stable, and more comprehensible? The book explores these questions, pursuing an approach closely linked to real-world applications.

The book is intended for three main categories of readers: (1) management-level employees of companies operating in the financial markets, banks, insurance operators, portfolio managers, brokers, risk assessors, investment managers, and debt managers; (2) policymakers and regulators for financial markets, from government technicians to politicians; and (3) readers curious about technology, both for professional and private purposes, as well as those involved in innovation and research in the private and public spheres.

Explains the links between AI and finance through application examples Shows how technology can make markets safer and more profitable Links the financial dynamics to the dynamics of the COVID-19 pandemic

Autorentext

Federico Cecconi is a senior researcher at ISTC, Institute of Cognitive Sciences and Technologies of CNR, Rome (LABSS-Laboratory on Agent-Based Social Simulation).

He teaches "Informatics" and "Numerical Methods" at Libera Università Maria SS. Assunta (LUMSA). He is the author of numerous books on agent-based social simulation. His research interests are in the field of financial modelling, dynamics of complex networks, microeconomic modelling through agent-based simulation.

Inhalt

Chapter 1. Artificial Intelligence and Financial Markets.- Chapter 2. AI, the overall picture.- Chapter 3. Financial markets: values, dynamics, problems.- Chapter 4. The AI's Role in the Great Reset.- Chapter 5. AI Fintech: find out the truth.- Chapter 6. ABM applications to Financial Markets.- Chapter 7. ML application to the Financial Market.- Chapter 8. AI tools for pricing of distressed asset utp and npl loan portfolios.- Chapter 9. More than data science: FuturICT 2.0.- Chapter 10. Opinion dynamics.

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