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This book provides the first extensive analytic comparison between models and results from econophysics and financial economics in an accessible and common vocabulary. Unlike other publications dedicated to econophysics, it situates this field in the evolution of financial economics by laying the foundations for common theoretical framework and models.
There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure.
Agricultural, energy or mineral commodities are traded internationally in two market categories: physical markets and financial markets. More specifically, on the financial markets, contracts are negotiated, the price of which depends on the price of a commodity. These contracts are called derivatives (futures, options contracts, swaps). This book presents, on the one hand, the characteristics of these derivatives and the markets on which they are traded and, on the other hand, those transactions that typically combine an action on the physical market and a transaction on the corresponding financial market. The understanding of commodity financial markets mainly relies on the resources of economic analysis, especially the financial economy, because the use of this discipline is essential to understanding the major operations that are conducted daily by the operators of these markets: traders, producers, processors, financiers.
We all know the hard fact: neither wealth nor income is ever uniform for us all. Justified or not, they are unevenly distributed; few are rich and many are poor! Investigations for more than hundred years and the recent availability of the income distribution data in the internet (made available by the finance ministries of various countries; from the tax return data of the income tax departments) have revealed some remarkable features. Irrespective of many differences in culture, history, language and, to some extent, the economic policies followed in different countries, the income distribution is seen to fol low a particular universal pattern. So does the wealth distribution. Barring an initial rise in population with income (or wealth; for the destitutes), the population decreases either exponentially or in a log-normal way for the ma jority of 'middle income' group, and it eventually decreases following a power law (Pareto law, following Vilfredo Pareto's observation in 1896) for the rich est 5-10 % of the population! This seems to be an universal feature - valid for most of the countries and civilizations; may be in ancient Egypt as well! Econophysicists tried to view this as a natural law for a statistical ma- body-dynamical market system, analogous to gases, liquids or solids: classical or quantum.
This second edition presents the advances made in finance market analysis since 2005. The book provides a careful introduction to stochastic methods along with approximate ensembles for a single, historic time series. The new edition explains the history leading up to the biggest economic disaster of the 21st century. Empirical evidence for finance market instability under deregulation is given, together with a history of the explosion of the US Dollar worldwide. A model shows how bounds set by a central bank stabilized FX in the gold standard era, illustrating the effect of regulations. The book presents economic and finance theory thoroughly and critically, including rational expectations, cointegration and arch/garch methods, and replaces several of those misconceptions by empirically based ideas. This book will be of interest to finance theorists, traders, economists, physicists and engineers, and leads the reader to the frontier of research in time series analysis.
This book reflects the state of the art on nonlinear economic dynamics, financial market modelling and quantitative finance. It contains eighteen papers with topics ranging from disequilibrium macroeconomics, monetary dynamics, monopoly, financial market and limit order market models with boundedly rational heterogeneous agents to estimation, time series modelling and empirical analysis and from risk management of interest-rate products, futures price volatility and American option pricing with stochastic volatility to evaluation of risk and derivatives of electricity market. The book illustrates some of the most recent research tools in these areas and will be of interest to economists working in economic dynamics and financial market modelling, to mathematicians who are interested in applying complexity theory to economics and finance and to market practitioners and researchers in quantitative finance interested in limit order, futures and electricity market modelling, derivative pricing and risk management.
This book introduces an analytically tractable and computationally effective class of non-Gaussian models for shocks (regular L‚vy processes of the exponential type) and related analytical methods similar to the initial Merton-Black-Scholes approach, which the authors call the Merton-Black-Scholes theory.The authors have chosen applications interesting for financial engineers and specialists in financial economics, real options, and partial differential equations (especially pseudodifferential operators); specialists in stochastic processes will benefit from the use of the pseudodifferential operators technique in non-Gaussian situations. The authors also consider discrete time analogues of perpetual American options and the problem of the optimal choice of capital, and outline several possible directions in which the methods of the book can be developed further.Taking account of a diverse audience, the book has been written in such a way that it is simple at the beginning and more technical in further chapters, so that it is accessible to graduate students in relevant areas and mathematicians without prior knowledge of finance or economics.
The remarkable evolution of econophysics research has brought the deep synthesis of ideas derived from economics and physics to subjects as diverse as education, banking, finance, and the administration of large institutions. The original papers in this collection present a broad summary of these advances, written by interdisciplinary specialists. Included are studies on subjects in the development of econophysics; on the perspectives offered by econophysics on large problems in economics and finance, including the 2008-9 financial crisis; and on higher education and group decision making. The introductions and insights they provide will benefit everyone interested in applications of this new transdisciplinary science. Ten papers present an updated version of the origins, issues, and applications of econophysics Economics and finance chapters consider lessons learned from the 2008-9 financial crisis Sociophysics chapters propose new thinking on educational reforms and group decision making
This book discusses the study and analysis of the physical aspects of social systems and models, inspired by the analogy with familiar models of physical systems and possible applications of statistical physics tools. Unlike the traditional analysis of the physics of macroscopic many-body or condensed matter systems, which is now an established and mature subject, the upsurge in the physical analysis and modelling of social systems, which are clearly many-body dynamical systems, is a recent phenomenon. Though the major developments in sociophysics have taken place only recently, the earliest attempts of proposing "Social Physics" as a discipline are more than one and a half centuries old. Various developments in the mainstream physics of condensed matter systems have inspired and induced the recent growth of sociophysical analysis and models. In spite of the tremendous efforts of many scientists in recent years, the subject is still in its infancy and major challenges are yet to be taken up. An introduction to these challenges is the main motivation for this book.
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.