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A continuous time random walk model for financial distributions

Author

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  • Jaume Masoliver
  • Miquel Montero
  • George H. Weiss

Abstract

We apply the formalism of the continuous time random walk to the study of financial data. The entire distribution of prices can be obtained once two auxiliary densities are known. These are the probability densities for the pausing time between successive jumps and the corresponding probability density for the magnitude of a jump. We have applied the formalism to data on the US dollar/Deutsche Mark future exchange, finding good agreement between theory and the observed data.

Suggested Citation

  • Jaume Masoliver & Miquel Montero & George H. Weiss, 2002. "A continuous time random walk model for financial distributions," Papers cond-mat/0210513, arXiv.org.
  • Handle: RePEc:arx:papers:cond-mat/0210513
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    Citations

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    Cited by:

    1. Sazuka, Naoya & Inoue, Jun-ichi & Scalas, Enrico, 2009. "The distribution of first-passage times and durations in FOREX and future markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2839-2853.
    2. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    3. James Primbs & Muruhan Rathinam, 2009. "Trader Behavior and its Effect on Asset Price Dynamics," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(2), pages 151-181.
    4. Zachary R. Fox & Eli Barkai & Diego Krapf, 2021. "Aging power spectrum of membrane protein transport and other subordinated random walks," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    5. Enrico Scalas, 2006. "Five Years of Continuous-time Random Walks in Econophysics," Lecture Notes in Economics and Mathematical Systems, in: Akira Namatame & Taisei Kaizouji & Yuuji Aruka (ed.), The Complex Networks of Economic Interactions, pages 3-16, Springer.
    6. Enrico Scalas & Rudolf Gorenflo & Hugh Luckock & Francesco Mainardi & Maurizio Mantelli & Marco Raberto, 2004. "Anomalous waiting times in high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 695-702.
    7. 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.
    8. Plamen Ch Ivanov & Ainslie Yuen & Pandelis Perakakis, 2014. "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    9. Scalas, Enrico & Kaizoji, Taisei & Kirchler, Michael & Huber, Jürgen & Tedeschi, Alessandra, 2006. "Waiting times between orders and trades in double-auction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 463-471.
    10. Schumer, Rina & Baeumer, Boris & Meerschaert, Mark M., 2011. "Extremal behavior of a coupled continuous time random walk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(3), pages 505-511.
    11. Masoliver, Jaume & Montero, Miquel & Perello, Josep & Weiss, George H., 2006. "The continuous time random walk formalism in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 577-598, December.
    12. Ni, Xiao-Hui & Jiang, Zhi-Qiang & Gu, Gao-Feng & Ren, Fei & Chen, Wei & Zhou, Wei-Xing, 2010. "Scaling and memory in the non-Poisson process of limit order cancelation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2751-2761.
    13. Javier Villarroel & Miquel Montero, 2008. "On properties of Continuous-Time Random Walks with Non-Poissonian jump-times," Papers 0812.2148, arXiv.org.
    14. Ponta, Linda & Trinh, Mailan & Raberto, Marco & Scalas, Enrico & Cincotti, Silvano, 2019. "Modeling non-stationarities in high-frequency financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 173-196.
    15. Scalas, Enrico, 2006. "The application of continuous-time random walks in finance and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 225-239.
    16. Vallois, Pierre & Tapiero, Charles S., 2007. "Memory-based persistence in a counting random walk process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 303-317.
    17. Guo, Gang & Chen, Bin & Zhao, Xinjun & Zhao, Fang & Wang, Quanmin, 2015. "First passage time distribution of a modified fractional diffusion equation in the semi-infinite interval," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 279-290.
    18. Villarroel, Javier & Montero, Miquel, 2009. "On properties of continuous-time random walks with non-Poissonian jump-times," Chaos, Solitons & Fractals, Elsevier, vol. 42(1), pages 128-137.
    19. Scalas, Enrico & Viles, Noèlia, 2014. "A functional limit theorem for stochastic integrals driven by a time-changed symmetric α-stable Lévy process," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 385-410.
    20. Jaros{l}aw Klamut & Tomasz Gubiec, 2018. "Directed Continuous-Time Random Walk with memory," Papers 1807.01934, arXiv.org.
    21. Gubiec, T. & Wiliński, M., 2015. "Intra-day variability of the stock market activity versus stationarity of the financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 216-221.
    22. Lv, Longjin & Xiao, Jianbin & Fan, Liangzhong & Ren, Fuyao, 2016. "Correlated continuous time random walk and option pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 100-107.

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