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.     

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.     

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.     

Psychophysics of time perception and valuation in temporal discounting of gain and loss

Anomalies in intertemporal choice (e.g. “hyperbolic” discounting and sign effect) have been investigated in econophysics and behavioral neuroeconomics. We experimentally examined the roles of psychophysical effects of time perception and subjective valuation of outcomes (value function) on temporal discounting of gain and loss, by utilizing a q$q$-exponential temporal discounting model developed in Tsallis’s thermostatistics. Consequently, we demonstrated that both “hyperbolic” discounting and the sign effect (i.e. gain is more steeply time-discounted than loss) are due to psychophysical effects of time perception (i.e., nonlinearity and gain–loss asymmetry). Implications of the present study for neuroeconomics and econophysics are discussed.     

经济研究中的物理学

当前的金融危机再次表明,传统经济学作为一门学科缺乏解释力和预测力.造成这个令人失望的状况的根本原因是由于经济学家没有按照科学的范式来发展这个学科.经济学的现状吸引了一群物理学家进入这个学科并形成了一个新的交叉学科——经济物理学,人们期望它在促进经济学科学化的进程中起决定性作用.文章首先简要介绍了经济学的主要内容,说明经济学理论是建立在理性和均衡假定基础之上的;接着论述了为什么经济学还不是一门科学,指出经济学研究不是基于逻辑实证主义原则来开展的;文章还分析了物理学家是如何研究经济问题的,介绍了经济物理学的主要研究内容和研究方法;文章最后提出经济学范式的转变必须从观察和实验出发,经济学理论必须建立在一个合理设计的量纲体系和对实际经济运行过程的正确理解基础之上.     

Stokes integral of economic growth: Calculus and the Solow model

Economic growth depends on capital and labor and two-dimensional calculus has been applied to economic theory. This leads to Riemann and Stokes integrals and to the first and second laws of production and growth. The mathematical structure is the same as in thermodynamics, economic properties may be related to physical terms: capital to energy, production to physical work, GDP per capita to temperature, production function to entropy. This is called econophysics. Production, trade and banking may be compared to motors, heat pumps or refrigerators. The Carnot process of the first law creates two levels in each system: cold and hot in physics; buyer and seller, investor and saver, rich and poor in economics. The efficiency rises with the income difference of rich and poor. The results of econophysics are compared to neoclassical theory.     

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.     

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.     

Dynamics of a quantum phase transition and relaxation to a steady state

We review recent theoretical work on two closely related issues: excitation of an isolated quantum condensed matter system driven adiabatically across a continuous quantum phase transition or a gapless phase, and apparent relaxation of an excited system after a sudden quench of a parameter in its Hamiltonian. Accordingly, the review is divided into two parts. The first part revolves around a quantum version of the Kibble–Zurek mechanism including also phenomena that go beyond this simple paradigm. What they have in common is that excitation of a gapless many-body system scales with a power of the driving rate. The second part attempts a systematic presentation of recent results and conjectures on apparent relaxation of a pure state of an isolated quantum many-body system after its excitation by a sudden quench. This research is motivated in part by recent experimental developments in the physics of ultracold atoms with potential applications in the adiabatic quantum state preparation and quantum computation.     

Memory and Markov Blankets

In theoretical biology, we are often interested in random dynamical systems—like the brain—that appear to model their environments. This can be formalized by appealing to the existence of a (possibly non-equilibrium) steady state, whose density preserves a conditional independence between a biological entity and its surroundings. From this perspective, the conditioning set, or Markov blanket, induces a form of vicarious synchrony between creature and world—as if one were modelling the other. However, this results in an apparent paradox. If all conditional dependencies between a system and its surroundings depend upon the blanket, how do we account for the mnemonic capacity of living systems? It might appear that any shared dependence upon past blanket states violates the independence condition, as the variables on either side of the blanket now share information not available from the current blanket state. This paper aims to resolve this paradox, and to demonstrate that conditional independence does not preclude memory. Our argument rests upon drawing a distinction between the dependencies implied by a steady state density, and the density dynamics of the system conditioned upon its configuration at a previous time. The interesting question then becomes: What determines the length of time required for a stochastic system to ‘forget’ its initial conditions? We explore this question for an example system, whose steady state density possesses a Markov blanket, through simple numerical analyses. We conclude with a discussion of the relevance for memory in cognitive systems like us.     

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.     

一个描述金融投资项目演化的量子力学状态方程

本文提出了一个描述金融投资项目演化的量子力学状态方程,该方程的参数比较好地模拟了金融市场的基本要素,包括投资(输入)、资产损耗(缩水)、资产增益、和收益(输出)等,方程中的量子力学算符也能够反映该项目的动力学过程与特征,所以能代表一类金融投资项目(其状态用Dirac符号表示)在市场中的演化模式.通过引入纠缠态表象得出了该方程的量子解(算符之和形式),该量子解给出了初态与终态的联系,也就给出了投资项目的动态过程.作为例子,求出单一投资项目在金融市场中的演化,不但得出了符合市场演化趋势的解,而且提出了二项-负二项纠缠态.在推导过程中,充分利用了Dirac符号和有序算符内的积分技术(IWOP).     

The Natural Philosophy of Economic Information: Autonomous Agents and Physiosemiosis

Information is a core concept in modern economics, yet its definition and empirical specification is elusive. One reason is the intellectual grip of the Shannon paradigm which marginalizes semantic information. However, a precise concept of economic information must be based on a theory of semantics, since what counts economically is the meaning, function and use of information. This paper introduces a new principled approach to information that adopts the paradigm of biosemiotics, rooted in the philosophy of Charles S. Peirce and builds on recent developments of the thermodynamics of information. Information processing by autonomous agents, defined as autopoietic heat engines, is conceived as physiosemiosis operating according to fundamental thermodynamic principles of information processing, as elucidated in recent work by Kolchinsky and Wolpert (KW). I plug the KW approach into a basic conceptual model of physiosemiosis and present an evolutionary interpretation. This approach has far-reaching implications for economics, such as suggesting an evolutionary view of the economic agent, choice and behavior, which is informed by applications of statistical thermodynamics on the brain.     

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.     

金融物理的若干基本问题与研究进展(Ⅱ)--基于经纪人的动力学模型的建模与分析

一门全新的交叉学科金融物理研究的第二种处理方法是构建金融市场物理模型，文章对其基本观点作了简介，并重点介绍了金融市场中基于经纪人的动力学模型的建模与分析，阐述了物理学在21世纪的金融工程研究中可发挥的作用与意义。     

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.     

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.     

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 probabilistic choice model based on Tsallis’ statistics

Decision under risk and uncertainty (probabilistic choice) has been attracting attention in econophysics and neuroeconomics. This paper proposes a probabilistic choice model based on a mathematical equivalence of delay and uncertainty in decision-making, and the deformed algebra developed in the Tsallis’ non-extensive thermodynamics. Furthermore, it is shown that this model can be utilized to quantify the degree of consistency in probabilistic choice in humans and animals. Future directions in the application of the model to studies in econophysics, neurofinance, neuroeconomics, and social physics are discussed.