This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

On the trading floor, all action is based on news, therefore rumors in financial markets are an everyday phenomenon. Rumors are the oldest mass medium in the world and their nature is still difficult to grasp. Scientifically, not much is known about rumors, especially in the financial markets, where their consequences can have real money consequences. Rumors in Financial Markets provides a fresh insight to the topic, combining the theory of Behavioral Finance with that of Experimental Finance--a new and innovative scientific method which observes real decision makers in a controlled, clearly structured environment. Using the results from surveys and experiments, the author argues that rumors in the context of financial markets are built on three cornerstones: Finance, Psychology and Sociology. The book provides insights into how rumors evolve, spread and are traded on and provides explanations as to why volatility rockets, strong price movements, herding behavior for example, occur for apparently no good reason.

This visionary book takes stock of the urgent challenges facing food chains globally and provides a critical evaluation of radical new thinking and perspectives on agricultural and food policy. Wyn Grant investigates the principal drivers of change in food and agriculture, including globalization, climate change, the structure of the industry, changing patterns of consumer demand and new technologies.

Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.

Many questions have been raised about America's status in the increasingly interconnected global economy. Yet key factsâ€"such as the amount of foreign assets abroad owned by U.S. citizensâ€"are not known. The crucial data needed to assess the U.S. position are unavailable. This volume explores significant shortcomings in U.S. data on international capital transactions and their implications for policymakers. The volume offers clearcut recommendations for U.S. agencies to bring data collection and analyses of the global economy into the twenty-first century. The volume explores: How factors emerging since the early 1980s have shaped world financial markets and revealed shortcomings in data collection and analysis. How the existing U.S. data system works and where it fails how measurements of international financial transactions are recorded; and how swaps, options, and futures present special reporting problems. How alternative methods, such as collecting data, from sources such as global custodians and international clearinghouses, might improve coverage and accuracy.

A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.