An innovative feature of this book is its econocentric structure, focusing on digital designs. From the outset, econocentrism is assumed to be a core engine of capitalism, like money. The new coronavirus pandemic has changed lifestyles worldwide, which are unlikely ever to return in their original form. This great transformation will change the nature of the socio-economic system itself and will be centered on digital designs. At present, money already is beginning to undergo a major revolution in that sense. Many books dealing with digital designs and innovations have been published, but few if any of them focus on monetary and analytical methods in the way that this present volume does.
The book then contains 6 parts: Evolution of money and thinking complexities in the AI era; Goods market and the future of labor market; Computational social approaches to social dilemmas, smart city, cryptocurrencies; Artificial market experiments; The randomness and high frequencies in financial data; Other trading strategy issues and the effects of AI usage. These issues may be indispensable subjects in our age. Study these subject, and have a step forward to the future society!
Chapter 1.- A step forward to the future society.- Part 1: Evolution of
money and thinking complexities in the AI era.
Chapter 2: 'Good Money Drives
Out Bad' among Diversifying e-moneys: Cryptocurrency, Stablecoin, and Digital
Community Currency.
Chapter 3: Practical case study About US:
Doreming.- Part 2: Good market and the future of labor market.- Chapter 4:
Model Structure of Agent-Based Artificial Economic System Responsible for
Reproducing Fundamental Economic Behavior of Goods Market.
Chapter 5: AI and
the Future of the Labor Market: The Advent of a New Paradigm?.- Part 3:
Computational social approaches to social dilemmas, smart city,
cryptographics.- Chapter 6: Mathematical framework to quantify social
dilemmas.
Chapter 7: Agent-based Simulation for Service and Social Systems
and Large-scale Social Simulation Framework.
Chapter 8: Characterization of
XRP Crypto-asset Transactions from Networks Scientific Approach.- Part 4:
Artificial market experiments.
Chapter 9: The emergence of markets and
artificial market experiments.
Chapter 10: Trading Agents for Artificial
Futures Markets.
Chapter 11: Default Agent Set for Artificial Futures Market
Simulation.
Chapter 12: Programmed trading agents and market microstructure
in an artificial futures market.
Chapter 13: Artificial Intelligence (AI)
for financial markets: a good AI for designing better financial markets and a
bad AI for manipulating markets.- Part 5: The randomness and high frequencies
in the financial data.- Chapter 14: Possible Relationship of the Randomness
and the Stock Performance.
Chapter 15: Random Matrix Theory (RMT)
application on financial data.
Chapter 16: How does the entropy function
explain the distribution of high frequency data?.- Part 6: Other trading
strategy issues and the effects of AI usage.
Chapter 17: The Emergence of
Periodic Properties of Ordering Strategies under Disruption in the Beer
Game.
Chapter 18: Network of investment-oriented social media.
Chapter
19: Student Learning in the Age of AI.
Yuji Aruka, Professor Emeritus, Chuo University
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