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Singular Stochastic Differential Equations for Time Evolution of Stocks Within Non-white Noise Approach

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  • L. L. B. Miranda

    (Federal Education Center for Technological Education of Minas Gerais)

  • L. S. Lima

    (Federal Education Center for Technological Education of Minas Gerais)

Abstract

The influence of non-linear terms and non-white noise terms on stochastic differential equation model for time evolution of prices of the market is investigated with aim to analyse the effect generated on exponent of the long-tail distribution of the probability density of the returns and Hurst index. In particular, whether the model proposed is adequate as a possible mathematical model for description of the market either if it satisfies to the stylized facts obeyed by the financial markets as the long-tail distribution of the returns, which must obey to the inverse cubic law observed.

Suggested Citation

  • L. L. B. Miranda & L. S. Lima, 2024. "Singular Stochastic Differential Equations for Time Evolution of Stocks Within Non-white Noise Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2685-2694, November.
  • Handle: RePEc:kap:compec:v:64:y:2024:i:5:d:10.1007_s10614-023-10516-x
    DOI: 10.1007/s10614-023-10516-x
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    as
    1. Hao Meng & Fei Ren & Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei-Xing Zhou & Wei Zhang, 2012. "Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations," Papers 1201.2825, arXiv.org.
    2. G.-F. Gu & W.-X. Zhou, 2009. "On the probability distribution of stock returns in the Mike-Farmer model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(4), pages 585-592, February.
    3. Stanis{l}aw Dro.zd.z & Robert Gk{e}barowski & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marcin Wk{a}torek, 2018. "Bitcoin market route to maturity? Evidence from return fluctuations, temporal correlations and multiscaling effects," Papers 1804.05916, arXiv.org, revised Jul 2018.
    4. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    5. in ׳t Veld, Daan, 2016. "Adverse effects of leverage and short-selling constraints in a financial market model with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 45-67.
    6. Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
    7. Lima, L.S., 2017. "Modeling of the financial market using the two-dimensional anisotropic Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 544-551.
    8. S. Drozdz & J. Kwapien & F. Gruemmer & F. Ruf & J. Speth, 2002. "Are the contemporary financial fluctuations sooner converging to normal?," Papers cond-mat/0208240, arXiv.org, revised Jul 2003.
    9. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Pawe{l} O'swic{e}cimka & Marek Stanuszek, 2018. "Multifractal cross-correlations between the World Oil and other Financial Markets in 2012-2017," Papers 1812.08548, arXiv.org, revised Jun 2019.
    10. Xing, Dun-Zhong & Li, Hai-Feng & Li, Jiang-Cheng & Long, Chao, 2021. "Forecasting price of financial market crash via a new nonlinear potential GARCH model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    11. Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
    12. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
    13. Lima, Leonardo S. & Oliveira, S.C. & Abeilice, A.F. & Melgaço, J.H.C., 2019. "Breaks down of the modeling of the financial market with addition of non-linear terms in the Itô stochastic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    14. Lima, L.S. & Oliveira, S.C., 2020. "Two-dimensional stochastic dynamics as model for time evolution of the financial market," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    15. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    16. Xiaotao Zhang & Jing Ping & Tao Zhu & Yuelei Li & Xiong Xiong, 2016. "Are Price Limits Effective? An Examination of an Artificial Stock Market," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-21, August.
    17. Orlean, Andre, 1995. "Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 28(2), pages 257-274, October.
    18. Jean-Philippe Bouchaud & Rama Cont, 1998. "A Langevin approach to stock market fluctuations and crashes," Science & Finance (CFM) working paper archive 500027, Science & Finance, Capital Fund Management.
    19. W.-X. Zhou & D. Sornette, 2007. "Self-organizing Ising model of financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 175-181, January.
    20. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    21. Assenza, Tiziana & Delli Gatti, Domenico & Grazzini, Jakob, 2015. "Emergent dynamics of a macroeconomic agent based model with capital and credit," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 5-28.
    22. K. Sznajd-Weron & R. Weron, 2002. "A Simple Model Of Price Formation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 115-123.
    23. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    24. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    25. Parameswaran Gopikrishnan & Martin Meyer & Luis A Nunes Amaral & H Eugene Stanley, 1998. "Inverse Cubic Law for the Probability Distribution of Stock Price Variations," Papers cond-mat/9803374, arXiv.org, revised May 1998.
    26. Eugene F. Fama, 1963. "Mandelbrot and the Stable Paretian Hypothesis," The Journal of Business, University of Chicago Press, vol. 36, pages 420-420.
    27. Federico Botta & Helen Susannah Moat & H Eugene Stanley & Tobias Preis, 2015. "Quantifying Stock Return Distributions in Financial Markets," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-10, September.
    28. Gontis, V. & Ruseckas, J. & Kononovičius, A., 2010. "A long-range memory stochastic model of the return in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 100-106.
    29. Stanislaw Drozdz & Jaroslaw Kwapien & Pawel Oswiecimka & Rafal Rak, 2010. "The foreign exchange market: return distributions, multifractality, anomalous multifractality and Epps effect," Papers 1011.2385, arXiv.org.
    30. Ying-Hui Shao & Gao Feng Gu & Zhi-Qiang Jiang & Wei-Xing Zhou & Didier Sornette, 2012. "Comparing the performance of FA, DFA and DMA using different synthetic long-range correlated time series," Papers 1208.4158, arXiv.org.
    31. Jian Zhou & Gao-Feng Gu & Zhi-Qiang Jiang & Xiong Xiong & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2017. "Computational Experiments Successfully Predict the Emergence of Autocorrelations in Ultra-High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 579-594, December.
    32. Lima, L.S. & Miranda, L.L.B., 2018. "Price dynamics of the financial markets using the stochastic differential equation for a potential double well," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 828-833.
    33. Gao-Feng Gu & Wei-Xing Zhou, 2008. "Emergence of long memory in stock volatility from a modified Mike-Farmer model," Papers 0807.4639, arXiv.org, revised May 2009.
    34. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
    35. S. Drozdz & M. Forczek & J. Kwapien & P. Oswiecimka & R. Rak, 2007. "Stock market return distributions: from past to present," Papers 0704.0664, arXiv.org.
    36. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    37. Kononovicius, A. & Gontis, V., 2012. "Agent based reasoning for the non-linear stochastic models of long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1309-1314.
    38. P. Gopikrishnan & M. Meyer & L.A.N. Amaral & H.E. Stanley, 1998. "Inverse cubic law for the distribution of stock price variations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 3(2), pages 139-140, July.
    39. Wa̧torek, Marcin & Drożdż, Stanisław & Oświȩcimka, Paweł & Stanuszek, Marek, 2019. "Multifractal cross-correlations between the world oil and other financial markets in 2012–2017," Energy Economics, Elsevier, vol. 81(C), pages 874-885.
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    Price dynamics; Stylized facts;

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