This book rehabilitates beta as a definition of systemic risk by using particle physics to evaluate discrete components of financial risk. Much of the frustration with beta stems from the failure to disaggregate its discrete components; conventional beta is often treated as if it were "atomic" in the original Greek sense: uncut and indivisible. By analogy to the Standard Model of particle physics theory's three generations of matter and the three-way interaction of quarks, Chen divides beta as the fundamental unit of systemic financial risk into three matching pairs of "baryonic" components. The resulting econophysics of beta explains no fewer than three of the most significant anomalies and puzzles in mathematical finance. Moreover, the model's three-way analysis of systemic risk connects the mechanics of mathematical finance with phenomena usually attributed to behavioral influences on capital markets. Adding consideration of volatility and correlation, and of the distinct cash flow and discount rate components of systematic risk, harmonizes mathematical finance with labor markets, human capital, and macroeconomics.

Filling the gap for an up-to-date textbook in this relatively new interdisciplinary research field, this volume provides readers with a thorough and comprehensive introduction. Based on extensive teaching experience, it includes numerous worked examples and highlights in special biographical boxes some of the most outstanding personalities and their contributions to both physics and economics. The whole is rounded off by several appendices containing important background material.

This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.

What is Econophysics The discipline of econophysics is an unconventional interdisciplinary research field that applies ideas and methods that were initially established by physicists in order to tackle difficulties in economics. These challenges typically involve uncertainty or stochastic processes and nonlinear dynamics. It has also been referred to as statistical finance, which is a phrase that refers to its roots in statistical physics. Some of its applications to the study of financial markets involve statistical finance. There is a strong connection between econophysics and social physics. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Econophysics Chapter 2: Complex system Chapter 3: Fischer Black Chapter 4: El Farol Bar problem Chapter 5: Joseph L. McCauley Chapter 6: Thermoeconomics Chapter 7: Statistical finance Chapter 8: Complexity economics Chapter 9: J. Barkley Rosser Jr. Chapter 10: Institutionalist political economy Chapter 11: Didier Sornette Chapter 12: Jean-Philippe Bouchaud Chapter 13: Bikas Chakrabarti Chapter 14: Kinetic exchange models of markets Chapter 15: Quantitative analysis (finance) Chapter 16: Quantum finance Chapter 17: Mathematical finance Chapter 18: Dragon king theory Chapter 19: Physics of financial markets Chapter 20: Quantum economics Chapter 21: Tiziana Di Matteo (II) Answering the public top questions about econophysics. (III) Real world examples for the usage of econophysics in many fields. (IV) Rich glossary featuring over 1200 terms to unlock a comprehensive understanding of econophysics. (eBook only). Who will benefit Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of econophysics.

Economics requires understanding and analyzing forces that bring buyers and sellers to a market place who then negotiate exchanges of goods and services based on a mutually agreeable price. Economists have their own method of modeling whereby models are first conceived of some notion of economic and financial thinking, before being empirically tested, and anomalies are then recognized if the observed data is inconsistent with the hypothetical underpinning. This is in inherent contradiction with the modeling approaches of physicists who develop their theories, principle and laws after observing empirical data. The awareness that physics can enlighten the understanding of human behavior (and thus economics), and the interest of physicists in applying their training and models to understanding the complexities of finance and economics, led to the creation of a new field of study appropriately termed as Econophysics. Selected Topics on Econophysics is a collection of essays on topics that enhance and enrich our understanding of economic modeling when the same rigor of modelling used by physicists is brought to developing financial and economic theories. These articles include discussions on modeling bitcoins, stock index modeling using geometric Brownian motion, agent-based modeling, wealth distribution modeling, as well as modeling related to fractal regression, and chaotic processes. This interdisciplinary book will interest researchers, graduate students and professionals in the fields of economics, finance as well as physics.

This book presents the works and research findings of physicists, economists, mathematicians, statisticians, and financial engineers who have undertaken data-driven modelling of market dynamics and other empirical studies in the field of Econophysics. During recent decades, the financial market landscape has changed dramatically with the deregulation of markets and the growing complexity of products. The ever-increasing speed and decreasing costs of computational power and networks have led to the emergence of huge databases. The availability of these data should permit the development of models that are better founded empirically, and econophysicists have accordingly been advocating that one should rely primarily on the empirical observations in order to construct models and validate them. The recent turmoil in financial markets and the 2008 crash appear to offer a strong rationale for new models and approaches. The Econophysics community accordingly has an important future role to play in market modelling. The Econophys-Kolkata VIII conference proceedings are devoted to the presentation of many such modelling efforts and address recent developments. A number of leading researchers from across the globe report on their recent work, comment on the latest issues, and review the contemporary literature.

This survey of portfolio theory, from its modern origins through more sophisticated, “postmodern” incarnations, evaluates portfolio risk according to the first four moments of any statistical distribution: mean, variance, skewness, and excess kurtosis. In pursuit of financial models that more accurately describe abnormal markets and investor psychology, this book bifurcates beta on either side of mean returns. It then evaluates this traditional risk measure according to its relative volatility and correlation components. After specifying a four-moment capital asset pricing model, this book devotes special attention to measures of market risk in global banking regulation. Despite the deficiencies of modern portfolio theory, contemporary finance continues to rest on mean-variance optimization and the two-moment capital asset pricing model. The term postmodern portfolio theory captures many of the advances in financial learning since the original articulation of modern portfolio theory. A comprehensive approach to financial risk management must address all aspects of portfolio theory, from the beautiful symmetries of modern portfolio theory to the disturbing behavioral insights and the vastly expanded mathematical arsenal of the postmodern critique. Mastery of postmodern portfolio theory’s quantitative tools and behavioral insights holds the key to the efficient frontier of risk management.