Is econophysics a new discipline? The neopositivist argument

Econophysics is a new approach which applies various models and concepts associated with statistical physics to economic (and financial) phenomena. This field of research is a new step in the history and the evolution of Physics Sciences and the question about the disciplinary characteristics of this field must be asked. At first glance, it might appear that economics and econophysics share the same subject of research (that of analysis of economic reality). In this paper I will use neopositivism to show that econophysics is methodologically very different from economics and that it can be considered as a separate discipline. The neopositivist framework provides econophysics with some arguments for rejecting mainstream economics.     

Economic uncertainty and econophysics

The objective of this paper is to provide a methodological link between econophysics and economics. I will study a key notion of both fields: uncertainty and the ways of thinking about it developed by the two disciplines. After having presented the main economic theories of uncertainty (provided by Knight, Keynes and Hayek), I show how this notion is paradoxically excluded from the economic field. In economics, uncertainty is totally reduced by an a priori Gaussian framework—in contrast to econophysics, which does not use a priori models because it works directly on data. Uncertainty is then not shaped by a specific model, and is partially and temporally reduced as models improve. This way of thinking about uncertainty has echoes in the economic literature. By presenting econophysics as a Knightian method, and a complementary approach to a Hayekian framework, this paper shows that econophysics can be methodologically justified from an economic point of view.     

Econophysics and the Entropic Foundations of Economics

This paper examines relations between econophysics and the law of entropy as foundations of economic phenomena. Ontological entropy, where actual thermodynamic processes are involved in the flow of energy from the Sun through the biosphere and economy, is distinguished from metaphorical entropy, where similar mathematics used for modeling entropy is employed to model economic phenomena. Areas considered include general equilibrium theory, growth theory, business cycles, ecological economics, urban–regional economics, income and wealth distribution, and financial market dynamics. The power-law distributions studied by econophysicists can reflect anti-entropic forces is emphasized to show how entropic and anti-entropic forces can interact to drive economic dynamics, such as in the interaction between business cycles, financial markets, and income distributions.     

Ups and downs of economics and econophysics — Facebook forecast

What is econophysics and its relationship with economics? What is the state of economics after the global economic crisis, and is there a future for the paradigm of market equilibrium, with imaginary perfect competition and rational agents? Can the next paradigm of economics adopt important assumptions derived from econophysics models: that markets are chaotic systems, striving to extremes as bubbles and crashes show, with psychologically motivated, statistically predictable individual behaviors? Is the future of econophysics, as predicted here, to disappear and become a part of economics? A good test of the current state of econophysics and its methods is the valuation of Facebook immediately after the initial public offering — this forecast indicates that Facebook is highly overvalued, and its IPO valuation of 104 billion dollars is mostly the new financial bubble based on the expectations of unlimited growth, although it’s easy to prove that Facebook is close to the upper limit of its users.     

Sustainable Development and Spatial Inhomogeneities

Historical data, theory and computer simulations support a connection between growth and economic inequality. Our present world with large regional differences in economic activity is a result of fast economic growth during the last two centuries. Because of limits to growth we might expect a future world to develop differently with far less growth. The question that we here address is: “Would a world with a sustainable economy be less unequal?” We then develop integrated spatial economic models based on limited resources consumption and technical knowledge accumulation and study them by the way of computer simulations. When the only coupling between world regions is diffusion we do not observe any spatial unequality. By contrast, highly localized economic activities are maintained by global market mechanisms. Structures sizes are determined by transportation costs. Wide distributions of capital and production are also predicted in this regime.     

A unified framework for the pareto law and Matthew effect using scale-free networks

We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)∼m^-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.     

Recent progress in econophysics: Chaos,leverage, and business cycles as revealed by agent-based modeling and human experiments

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like “intelligence” remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents’ intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.     

一类分数阶混沌金融系统的复杂性演化研究

物理学理论与方法在经济与金融领域中的成功应用催生了一个新的科学分支——经济物理学(econophysics).分数阶微积分系统的复杂动力学现象受到了越来越多学者的关注.本文定性地分析一类分数阶混沌金融系统的均衡解的稳定性及Hopf分岔发生的条件,并运用亚当斯-巴什福斯-莫尔顿预估-校正的有限差分法,通过分岔图、相图和时间序列图对该系统的复杂性演化行为进行仿真研究. 关键词： 经济物理学 分数阶微分方程 金融模型 混沌     

Non-life insurance pricing: multi-agent model

We use the maximum entropy principle for the pricing of non-life insurance and recover the Bühlmann results for the economic premium principle. The concept of economic equilibrium is revised in this respect.Received: 10 June 2004, Published online: 26 November 2004PACS: 89.65.Gh Economics; econophysics, financial markets, business and management - 05.20.-y Classical statistical mechanics     

Special issue on Econophysics

What is “Econophysics"? Who is an “econophysicist"? The coining of a new scientific term, composed of the names of two fields, traditionally considered to be far from each other, brings new dreams to investigators, by mere virtue of a new ensemble of viewpoints. The term “econophysics" has revealed a kinship between the fields of physics and economics, which was not obvious before. The first officially recognized conference by a professional society on “econophysics", Applications of Physics to Financial Analysis (APFA, soon to become APFA1) was held in Dublin in 1999. Since then APFA and its companion meetings have begun to reveal new branches of research from the established pathways explored in applied statistical physics and thus economics (in particular finance). The analysis of fluctuations in financial data by new or modified techniques has led to new insights. Such analysis involves physicists looking for correlation between entities in financial matter in much the same way as they have done for physical systems in their laboratories. This approach leads to useful new methods and results in different outputs. The studies of phase transitions and non-equilibrium effects, including self-organisation have progressed the understanding of many physical phenomena. So why not use the same methodology in a field which is thought to be governed by sociology, psychology, politics and other so called softer science? The observations of deterministic chaos, scaling, in financial time series (tools such as recurrence, plots exploiting symmetries in pricing theory or the use of the wavelet or path integral or renormalisation group method) will still give some work ahead even though all these tools have a basic origin or are rather standard tools nowadays. Characterization of data and theory talks broke new ground in pursuit of e.g. useful strategies or political consequences. One continues to ask, how is it that fluctuations or other agents in a system conspire to give surprising anomalous properties? By broadening discussion to the category of econophysics topics, as covered in APFA2 (held in Liège, Belgium on July 13-15, 2000), we have gained new paradigms to study this question. Several reports to APFA2 are not included in the following to avoid duplicating reports in this proceedings. Very warm and profound acknowledgments are in order here. APFA2 was made possible mainly by the European Physical Society (EPS), the Fond National de la Recherche Scientifique (FNRS, Brussels), the Fonds voor Wetenschappelijk Onderzoek-Vlaanderen (FWO), and the University of Liège.     

Tsallis’ non-extensive free energy as a subjective value of an uncertain reward

Recent studies in neuroeconomics and econophysics revealed the importance of reward expectation in decision under uncertainty. Behavioral neuroeconomic studies have proposed that the unpredictability and the probability of an uncertain reward are distinctly encoded as entropy and a distorted probability weight, respectively, in the separate neural systems. However, previous behavioral economic and decision-theoretic models could not quantify reward-seeking and uncertainty aversion in a theoretically consistent manner. In this paper, we have: (i) proposed that generalized Helmholtz free energy in Tsallis’ non-extensive thermostatistics can be utilized to quantify a perceived value of an uncertain reward, and (ii) empirically examined the explanatory powers of the models. Future study directions in neuroeconomics and econophysics by utilizing the Tsallis’ free energy model are discussed.     

A social discounting model based on Tsallis’ statistics

Social decision making (e.g. social discounting and social preferences) has been attracting attention in economics, econophysics, social physics, behavioral psychology, and neuroeconomics. This paper proposes a novel social discounting model based on the deformed algebra developed in the Tsallis’ non-extensive thermostatistics. Furthermore, it is suggested that this model can be utilized to quantify the degree of consistency in social discounting in humans and analyze the relationships between behavioral tendencies in social discounting and other-regarding economic decision making under game-theoretic conditions. Future directions in the application of the model to studies in econophysics, neuroeconomics, and social physics, as well as real-world problems such as the supply of live organ donations, are discussed.     

Competition of Multi-Agent Systems: Analysis of a Three-Company Econophysics Model

A three-company econophysics model for competing multi-agent systems in a triangular lattice is analyzed using mean field theory for its phase diagram. Interpretations for the temperature, spin density and lattice structures are presented. Suggestions for the use of this model for econophysics in the context of multi-agent systems are made.     

The pyramidal life cycle of economic structures

The pyramidal character of life cycles of economic structures is empirically confirmed on the basis of official statistical data of the years 2003 and 2004. The ergodic hypothesis is applied as one of methods of economic forecasting in evolutionary economics, econophysics and applied researches.     

Cointegration of output, capital, labor, and energy

Cointegration analysis is applied to the linear combinations of the time series of (the logarithms of) output, capital, labor, and energy for Germany, Japan, and the USA since 1960. The computed cointegration vectors represent the output elasticities of the aggregate energy-dependent Cobb-Douglas function. The output elasticities give the economic weights of the production factors capital, labor, and energy. We find that they are for labor much smaller and for energy much larger than the cost shares of these factors. In standard economic theory output elasticities equal cost shares. Our heterodox findings support results obtained with LINEX production functions.     

Between complexity of modelling and modelling of complexity: An essay on econophysics

Econophysics is an emerging field dealing with complex systems and emergent properties. A deeper analysis of themes studied by econophysicists shows that research conducted in this field can be decomposed into two different computational approaches: “statistical econophysics” and “agent-based econophysics”. This methodological scission complicates the definition of the complexity used in econophysics. Therefore, this article aims to clarify what kind of emergences and complexities we can find in econophysics in order to better understand, on one hand, the current scientific modes of reasoning this new field provides; and on the other hand, the future methodological evolution of the field.     

Networks of equities in financial markets

We review the recent approach of correlation based networks of financial equities. We investigate portfolio of stocks at different time horizons, financial indices and volatility time series and we show that meaningful economic information can be extracted from noise dressed correlation matrices. We show that the method can be used to falsify widespread market models by directly comparing the topological properties of networks of real and artificial markets.Received: 26 November 2003, Published online: 14 May 2004PACS: 89.75.Fb Structures and organization in complex systems - 89.75.Hc Networks and genealogical trees - 89.65.Gh Economics; econophysics, financial markets, business and management     

金融物理的若干基本问题与研究进展(Ⅰ)--价格的统计分析与价格涨落的随机过程模型

金融物理学是物理学概念和方法应用于金融分析的一门新的交叉学科，近年来受到人们的广泛关注．文章简述了金融物理的研究方向和研究方法，重点讨论了价格涨落的统计分析和相关的物理模型．     

An almost linear stochastic map related to the particle system models of social sciences

We propose a stochastic map model of economic dynamics. In the past decade, an array of observations in economics has been investigated in the econophysics literature, a major example being the universal features of inequality in terms of income and wealth. Another area of enquiry is the formation of opinion in a society. The model proposed attempts to produce positively skewed distributions and power law distributions as has been observed in the real data of income and wealth. Also, it shows a non-trivial phase transition in the opinion of a society (opinion formation). A number of physical models also generate similar results. In particular, kinetic exchange models have been successful especially in this regard. Therefore, we compare the results obtained from these two approaches and discuss a number of new features and drawbacks of this model.     

Effects of saving and spending patterns on holding time distribution

The effects of saving and spending patterns on holding time distribution of money are investigated based on the ideal gas-like models. We show the steady-state distribution obeys an exponential law when the saving factor is set uniformly, and a power law when the saving factor is set diversely. The power distribution can also be obtained by proposing a new model where the preferential spending behavior is considered. The association of the distribution with the probability of money to be exchanged has also been discussed.Received: 4 September 2003, Published online: 19 November 2003PACS: 89.65.Gh Economics; econophysics, financial markets, business and management - 87.23.Ge Dynamics of social systems - 05.10.-a Computational methods in statistical physics and nonlinear dynamics - 02.50.-r Probability theory, stochastic processes, and statistics