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A dynamical model describing stock market price distributions

Author

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  • Masoliver, Jaume
  • Montero, Miquel
  • Porrà, Josep M

Abstract

High-frequency data in finance have led to a deeper understanding on probability distributions of market prices. Several facts seem to be well established by empirical evidence. Specifically, probability distributions have the following properties: (i) They are not Gaussian and their center is well adjusted by Lévy distributions. (ii) They are long-tailed but have finite moments of any order. (iii) They are self-similar on many time scales. Finally, (iv) at small time scales, price volatility follows a non-diffusive behavior. We extend Merton's ideas on speculative price formation and present a dynamical model resulting in a characteristic function that explains in a natural way all of the above features. The knowledge of such a distribution opens a new and useful way of quantifying financial risk. The results of the model agree – with high degree of accuracy – with empirical data taken from historical records of the Standard & Poor's 500 cash index.

Suggested Citation

  • Masoliver, Jaume & Montero, Miquel & Porrà, Josep M, 2000. "A dynamical model describing stock market price distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 559-567.
  • Handle: RePEc:eee:phsmap:v:283:y:2000:i:3:p:559-567
    DOI: 10.1016/S0378-4371(00)00117-5
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    Cited by:

    1. M A Sánchez-Granero & J E Trinidad-Segovia & J Clara-Rahola & A M Puertas & F J De las Nieves, 2017. "A model for foreign exchange markets based on glassy Brownian systems," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-22, December.
    2. Miquel Montero, 2021. "Predator–prey model for stock market fluctuations," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 29-57, January.
    3. Collan, Mikael, 2004. "Giga-Investments: Modelling the Valuation of Very Large Industrial Real Investments," MPRA Paper 4328, University Library of Munich, Germany.
    4. Zhuang, Xin-tian & Huang, Xiao-yuan & Sha, Yan-li, 2004. "Research on the fractal structure in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 293-305.

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