Langevin processes, agent models and socio-economic systems

被引:11
作者
Richmond, P [1 ]
Sabatelli, L [1 ]
机构
[1] Univ Dublin Trinity Coll, Dept Phys, Dublin 2, Ireland
关键词
statistical mechanics;
D O I
10.1016/j.physa.2004.01.007
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We review some approaches to the understanding of fluctuations of financial asset prices. Our approach builds on the development of a simple Langevin equation that characterises stochastic processes. This provides a unifying approach that allows first a straightforward description of the early approaches of Bachelier. We generalize the approach to stochastic equations that model interacting agents. The agent models recently advocated by Marsilli and Solomon are motivated. Using a simple change of variable, we show that the peer pressure model of Marsilli and the wealth dynamics model of Solomon are essentially equivalent. The methods are further shown to be consistent with a global free energy functional that invokes an entropy term based on the Boltzmann formula. There follows a brief digression on the Heston model that extends the simple model to one that, in the language of physics, exhibits a temperature this is subject to stochastic fluctuations. Mathematically the model corresponds to a Feller process. Dragulescu and Yakovenko have shown how the model yields some of the stylised features of asset prices. A more recent approach by Michael and Johnson maximised a Tsallis entropy function subject to simple constraints. They obtain a distribution function for financial returns that exhibits power law tails and which can describe the distribution of returns not only over low but also high frequencies (minute by minute) data for the Dow Jones index. We show how this approach can be developed from an agent model, where the simple Langevin process is now conditioned by local rather than global noise. Such local noise may of course be the origin of speculative frenzy or herding in the market place. The approach yields a BBGKY type hierarchy of equations for the system correlation functions. Of especial interest is that the results can be obtained from a new free energy functional similar to that mentioned above except that a Tsallis like entropy term replaces the Boltzmann entropy term. A mean field approximation yields the results of Michael and Johnson. We show how personal income data for Brazil, the US, Germany and the UK, analyzed recently by Borgas can be qualitatively understood by this approach. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:27 / 38
页数:12
相关论文
共 15 条
[1]  
Baxter M., 1996, Financial Calculus: An Introduction to Derivative Pricing
[2]  
BORGES EP, 2002, ARXIVCONDMAT0205520V
[3]  
CECCONI F, 2002, ASXIVCONDMAT0202212V
[4]   Langevin equation for the density of a system of interacting Langevin processes [J].
Dean, DS .
JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL, 1996, 29 (24) :L613-L617
[5]   A short account of a connection of power laws to the information entropy [J].
Dover, Y .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2004, 334 (3-4) :591-599
[6]  
DRAGULESCU AD, 2002, ARXIVCONDMAT0203046V
[7]  
Johnson N.F., 2003, Financial Market Complexity
[8]  
KOZUKI N, 2002, ARXIVCONDMAT0210090V
[9]  
KRAWIECKI A, 2002, ARXIVCONDMAT0210044V
[10]  
LOUZOUN Y, 2001, ARXIVCONDMAT0109493V