A Particle Model for the Herding Phenomena Induced by Dynamic Market Signals

In this paper, we study the herding phenomena in financial markets arising from the combined effect of (1) non-coordinated collective interactions between the market players and (2) concurrent reactions of market players to dynamic market signals. By interpreting the expected rate of return of an asset and the favorability on that asset as position and velocity in phase space, we construct an agent-based particle model for herding behavior in finance. We then define two types of herding functionals using this model, and show that they satisfy a Gronwall type estimate and a LaSalle type invariance property respectively, leading to the herding behavior of the market players. Various numerical tests are presented to numerically verify these results.

[1]  R. Spigler,et al.  The Kuramoto model: A simple paradigm for synchronization phenomena , 2005 .

[2]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[3]  Seung-Yeal Ha,et al.  On collision-avoiding initial configurations to Cucker-Smale type flocking models , 2012 .

[4]  Seung-Yeal Ha,et al.  On the complete synchronization of the Kuramoto phase model , 2010 .

[5]  Seung-Yeal Ha,et al.  Emergence of time-asymptotic flocking in a stochastic Cucker-Smale system , 2009 .

[6]  Massimo Fornasier,et al.  Particle, kinetic, and hydrodynamic models of swarming , 2010 .

[7]  Lara Trussardi,et al.  A kinetic equation for economic value estimation with irrationality and herding , 2016, 1601.03244.

[8]  D. Burini,et al.  Collective learning modeling based on the kinetic theory of active particles. , 2016, Physics of life reviews.

[9]  In Ho Lee Market Crashes and Informational Avalanches , 1999 .

[10]  H H Sills,et al.  What is the law? , 1982, Dental clinics of North America.

[11]  P. Degond,et al.  A Hierarchy of Heuristic-Based Models of Crowd Dynamics , 2013, 1304.1927.

[12]  M. Salmon,et al.  Market Stress and Herding , 2004 .

[13]  S. Bikhchandani,et al.  You have printed the following article : A Theory of Fads , Fashion , Custom , and Cultural Change as Informational Cascades , 2007 .

[14]  U. Krause A DISCRETE NONLINEAR AND NON–AUTONOMOUS MODEL OF CONSENSUS FORMATION , 2007 .

[15]  Jeongho Kim,et al.  A Kinetic Description for the Herding Behavior in Financial Market , 2019, Journal of Statistical Physics.

[16]  In Ho Lee Market Crashes and Informational Avalanches , 1998 .

[17]  E. Tadmor,et al.  From particle to kinetic and hydrodynamic descriptions of flocking , 2008, 0806.2182.

[18]  Markus K. Brunnermeier Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding , 2001 .

[19]  Seung-Yeal Ha,et al.  Emergent dynamics of the Cucker-Smale flocking model and its variants , 2016, 1604.04887.

[20]  C. Hemphill,et al.  The Law, Culture, and Economics of Fashion , 2009 .

[21]  Seung-Yeal Ha,et al.  A simple proof of the Cucker-Smale flocking dynamics and mean-field limit , 2009 .

[22]  Markus K. Brunnermeier Asset Pricing under Asymmetric Information , 2001 .

[23]  G. Parisi,et al.  FROM EMPIRICAL DATA TO INTER-INDIVIDUAL INTERACTIONS: UNVEILING THE RULES OF COLLECTIVE ANIMAL BEHAVIOR , 2010 .

[24]  Jesús Rosado,et al.  Asymptotic Flocking Dynamics for the Kinetic Cucker-Smale Model , 2010, SIAM J. Math. Anal..

[25]  Felipe Cucker,et al.  Emergent Behavior in Flocks , 2007, IEEE Transactions on Automatic Control.

[26]  R. C. Merton,et al.  Continuous-Time Finance , 1990 .

[27]  I. Welch,et al.  Rational herding in financial economics , 1996 .

[28]  J. P. Lasalle Some Extensions of Liapunov's Second Method , 1960 .

[29]  Yongsik Kim,et al.  APPLICATION OF FLOCKING MECHANISM TO THE MODELING OF STOCHASTIC VOLATILITY , 2013 .

[30]  Nancy L. Stokey,et al.  Information, Trade, and Common Knowledge , 1982 .

[31]  P. Alam ‘A’ , 2021, Composites Engineering: An A–Z Guide.

[32]  Andreas Flache,et al.  Understanding Complex Social Dynamics: A Plea For Cellular Automata Based Modelling , 1998, J. Artif. Soc. Soc. Simul..

[33]  J. Tirole On the Possibility of Speculation under Rational Expectations , 1982 .

[34]  Manuel S. Santos,et al.  Rational asset pricing bubbles , 1997 .

[35]  V. Akila,et al.  Information , 2001, The Lancet.

[36]  J. Toner,et al.  Flocks, herds, and schools: A quantitative theory of flocking , 1998, cond-mat/9804180.

[37]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[38]  Lorenzo Pareschi,et al.  Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences , 2010 .

[39]  S. Smale,et al.  On the mathematics of emergence , 2007 .

[40]  Pierre Degond,et al.  Continuum limit of self-driven particles with orientation interaction , 2007, 0710.0293.

[41]  C. Avery,et al.  Multidimensional Uncertainty and Herd Behavior in Financial Markets , 1998 .

[42]  M. Burger,et al.  Continuous limit of a crowd motion and herding model: Analysis and numerical simulations , 2011 .

[43]  Marcello Edoardo Delitala,et al.  A mathematical model for value estimation with public information and herding , 2013 .

[44]  Lamia Youseff,et al.  Discrete and continuous models of the dynamics of pelagic fish: Application to the capelin , 2008, Math. Comput. Simul..

[45]  G. Toscani,et al.  Kinetic models of opinion formation , 2006 .

[46]  Markus K. Brunnermeier,et al.  Bubbles and crashes , 2002 .

[47]  A. Bertozzi,et al.  Self-propelled particles with soft-core interactions: patterns, stability, and collapse. , 2006, Physical review letters.

[48]  Lorenzo Pareschi,et al.  Reviews , 2014 .

[49]  Nicola Bellomo,et al.  On the Modeling of Traffic and Crowds: A Survey of Models, Speculations, and Perspectives , 2011, SIAM Rev..

[50]  Eitan Tadmor,et al.  A New Model for Self-organized Dynamics and Its Flocking Behavior , 2011, 1102.5575.

[51]  Yongsik Kim,et al.  A mathematical model for volatility flocking with a regime switching mechanism in a stock market , 2015 .

[52]  Marco Ajmone Marsan,et al.  Towards a mathematical theory of complex socio-economical systems by functional subsystems representation , 2008 .

[53]  Young-Pil Choi,et al.  Sharp conditions to avoid collisions in singular Cucker-Smale interactions , 2016, 1609.03447.

[54]  Juan Soler,et al.  MULTISCALE BIOLOGICAL TISSUE MODELS AND FLUX-LIMITED CHEMOTAXIS FOR MULTICELLULAR GROWING SYSTEMS , 2010 .