Artificial Intelligence in Economics and Finance Theories

This book explores the integration of AI into economic and finance theories, redefining decision-making processes and enhancing understanding of uncertainties.

As Artificial Intelligence (AI) increasingly influences various facets of human life, a significant transformation is occurring in how we perceive and approach decision-making. Traditionally, individuals have leaned on established economics and finance theories to understand concepts such as comparative advantage, long-term economic growth, and the allocation of resources. However, there has been a noticeable gap in the literature regarding the integration of technological advancements into these foundational theories. The book Artificial Intelligence in Economics and Finance Theories addresses this gap by exploring how AI can enhance our understanding of economic and financial decision-making processes.

The essence of finance and economic theories lies in their ability to manage uncertainties, striving to bring future outcomes into the present. This principle is fundamentally linked to risk and risk management. By utilizing various models, both economics and finance aim to predict future events, while risk management seeks to mitigate uncertainties to achieve favorable results. Artificial Intelligence in Economics and Finance Theories delves into how AI can redefine essential economic and financial theories, especially those aimed at reducing uncertainties, thereby enabling agents to make more informed decisions.

Ultimately, the book posits that certain dimensions of finance and economic theories may remain incomplete without considering the role of AI. By leveraging simulated intelligence, machines can mimic human decision-making and even anticipate events more effectively, thanks to their capacity to analyze vast datasets. This innovative approach invites readers to reconsider traditional economic and financial frameworks in light of AI's capabilities.