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
Автор: Ragupathy Venkatachalam
Издательство: Springer
Год: 2023
Страниц: 331
Язык: английский
Формат: pdf (true), epub
Размер: 41.1 MB
This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, Computer Science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded. Algorithmic thinking is gradually becoming an indispensable feature of Economics and Finance. Computational modes of thinking increasingly influence how we model individuals, organisations, market interactions and macroeconomic dynamics. Consider some topics that are traditionally of interest to economists and scholars of finance: decision-making by economic actors; mechanisms through which agents learn, adapt and thrive in uncertain, complex environments; the impact of economic decisions by individuals, firms and institutions on others in an interconnected system; emergence and diffusion of innovations; understanding volatility in financial markets; modelling aggregate, macroeconomic dynamics and associated pathologies (inflation, unemployment, inequality); and modes of exercising control through policy. All these issues are being studied using computational methods to varying degrees within the field.