Boltzmann-type models for price formation in the presence of behavioral aspects

Carlo  Brugna; Giuseppe Toscani; Carlo  Brugna; Giuseppe Toscani

doi:10.3934/nhm.2015.10.543

Networks and Heterogeneous Media

2015, Volume 10, Issue 3: 543-557. doi: 10.3934/nhm.2015.10.543

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Boltzmann-type models for price formation in the presence of behavioral aspects

Carlo Brugna ^{1
,},
Giuseppe Toscani ^{2
,}

1.
Department of Physics, Via Bassi, 6, 27100 Pavia
2.
University of Pavia, Department of Mathematics, Via Ferrata 1, 27100 Pavia

Received: 01 August 2014 Revised: 01 January 2015
Primary: 35B40, 91B60; Secondary: 82C40.

We introduce and discuss a new kinetic system for a financial market composed by agents that may belong to two different trader populations, whose behavior determines the price dynamic of a certain stock. Our mesoscopic description is based on the microscopic Lux--Marchesi model [16,17], and share analogies with the recent kinetic model by Maldarella and Pareschi [18], from which it differs in various points. In particular, it takes into account price acceleration, as well as a microscopic binary interaction for the exchange between the two populations of agents. Various numerical simulations show that the model can describe realistic situations, like regimes of boom and crashes, as well as the invariance of the large-time behavior with respect to the number of agents of the market.
- Kinetic models,
- markets and trades,
- multi-agent systems,
- opinion formation
Citation: Carlo Brugna, Giuseppe Toscani. Boltzmann-type models for price formation in the presence of behavioral aspects[J]. Networks and Heterogeneous Media, 2015, 10(3): 543-557. doi: 10.3934/nhm.2015.10.543

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Abstract

We introduce and discuss a new kinetic system for a financial market composed by agents that may belong to two different trader populations, whose behavior determines the price dynamic of a certain stock. Our mesoscopic description is based on the microscopic Lux--Marchesi model [16,17], and share analogies with the recent kinetic model by Maldarella and Pareschi [18], from which it differs in various points. In particular, it takes into account price acceleration, as well as a microscopic binary interaction for the exchange between the two populations of agents. Various numerical simulations show that the model can describe realistic situations, like regimes of boom and crashes, as well as the invariance of the large-time behavior with respect to the number of agents of the market.

References

[1]	R. Bapna, W. Jank and G. Shmueli, Price formation and its dynamics in online auctions, Decision Support Systems, 44 (2008), 641-656.
[2]	A. Chakraborti, Distributions of money in models of market economy, Int. J. Modern Phys. C, 13 (2002), 1315-1321. doi: 10.1142/S0129183102003905
[3]	A. Chakraborti and B. K. Chakrabarti, Statistical mechanics of money: Effects of saving propensity, Eur. Phys. J. B, 17 (2000), 167-170.
[4]	A. Chatterjee, B. K. Chakrabarti and S. S. Manna, Pareto law in a kinetic model of market with random saving propensity, Physica A, 335 (2004), 155-163. doi: 10.1016/j.physa.2003.11.014
[5]	A. Chatterjee, S. Yarlagadda and B. K. Chakrabarti, Eds., Econophysics of Wealth Distributions, New Economic Window Series, Springer-Verlag, Milan, 2005.
[6]	A. Chatterjee, B. K. Chakrabarti and R. B. Stinchcombe, Master equation for a kinetic model of trading market and its analytic solution, Phys. Rev. E, 72 (2005), 026126. doi: 10.1103/PhysRevE.72.026126
[7]	S. Cordier, L. Pareschi and G. Toscani, On a kinetic model for a simple market economy, J. Stat. Phys., 120 (2005), 253-277. doi: 10.1007/s10955-005-5456-0
[8]	M. Cristelli, L. Pietronero and A. Zaccaria, Critical overview of agent-based models for economics, in Proceedings of the School of Physics E. Fermi, course CLXXVI, Varenna, 2010. E-Print: arXiv:1101.1847.
[9]	A. Drăgulescu and V. M. Yakovenko, Statistical mechanics of money, Eur. Phys. Jour. B, 17 (2000), 723-729.
[10]	B. Düring, D. Matthes and G. Toscani, Kinetic equations modelling wealth redistribution: A comparison of approaches, Phys. Rev. E, 78 (2008), 056103. doi: 10.1103/PhysRevE.78.056103
[11]	B. Düring, D. Matthes and G. Toscani, A Boltzmann type approach to the formation of wealth distribution curves, Riv. Mat. Univ. Parma, 1 (2009), 199-261.
[12]	D. Kahneman and A. Tversky, Prospect theory: An analysis of decision under risk, Econometrica, 47 (1979), 183-214. doi: 10.1017/CBO9780511609220.014
[13]	D. Kahneman and A. Tversky, Choices, values, and frames, American Psychologist, 39 (1984), 341-350. doi: 10.1037/0003-066X.39.4.341
[14]	M. Levy, H. Levy and S. Solomon, Microscopic Simulation of Financial Markets: From Investor Behaviour to Market Phoenomena, Academic Press, San Diego, 2000.
[15]	T. Lux, The socio-economic dynamics of speculative markets: Interacting agents, chaos, and the fat tails of return distributions, Journal of Economic Behavior & Organization, 33 (1998), 143-165. doi: 10.1016/S0167-2681(97)00088-7
[16]	T. Lux and M. Marchesi, Volatility clustering in financial markets: A microscopic simulation of interacting agents, International Journal of Theoretical and Applied Finance, 3 (2000), 675-702. doi: 10.1142/S0219024900000826
[17]	T. Lux and M. Marchesi, Scaling and criticality in a stochastic multi-agent model of a financial market, Nature, 397 (1999), 498-500.
[18]	D. Maldarella and L. Pareschi, Kinetic models for socio-economic dynamics of speculative markets, Physica A, 391 (2012), 715-730. doi: 10.1016/j.physa.2011.08.013
[19]	R. N. Mantegna and H. E. Stanley, An Introduction to Econophysics Correlations and Complexity in Finance, Cambridge University Press, Cambridge, 2007.
[20]	D. Matthes and G. Toscani, On steady distributions of kinetic models of conservative economies, J. Stat. Phys., 130 (2008), 1087-1117. doi: 10.1007/s10955-007-9462-2
[21]	G. Naldi, L. Pareschi and G. Toscani, Eds., Mathematical Modelling of Collective Behavior in Socio-economic and Life Sciences, Birkhäuser, Boston, 2010. doi: 10.1007/978-0-8176-4946-3
[22]	L. Pareschi and G. Toscani, Interacting Multiagent Systems: Kinetic Equations and Monte Carlo Methods, Oxford University Press, Oxford, 2014.
[23]	L. Pareschi and G. Toscani, Wealth distribution and collective knowledge. A Boltzmann approach, Phil. Trans. R. Soc. A, 372 (2014), 20130396, 15pp. doi: 10.1098/rsta.2013.0396
[24]	F. Slanina, Inelastically scattering particles and wealth distribution in an open economy, Phys. Rev. E, 69 (2004), 046102. doi: 10.1103/PhysRevE.69.046102
[25]	G. Toscani, Kinetic models of opinion formation, Comm. Math. Scie., 4 (2006), 481-496. doi: 10.4310/CMS.2006.v4.n3.a1
[26]	J. Voit, The Statistical Mechanics of Financial Markets, Springer Verlag, Berlin, 2005.

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