IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1611.06407.html
   My bibliography  Save this paper

Interplay between endogenous and exogenous fluctuations in financial markets

Author

Listed:
  • Vygintas Gontis

Abstract

We address microscopic, agent based, and macroscopic, stochastic, modeling of the financial markets combining it with the exogenous noise. The interplay between the endogenous dynamics of agents and the exogenous noise is the primary mechanism responsible for the observed long-range dependence and statistical properties of high volatility return intervals. By exogenous noise we mean information flow or/and order flow fluctuations. Numerical results based on the proposed model reveal that the exogenous fluctuations have to be considered as indispensable part of comprehensive modeling of the financial markets.

Suggested Citation

  • Vygintas Gontis, 2016. "Interplay between endogenous and exogenous fluctuations in financial markets," Papers 1611.06407, arXiv.org.
    • Handle: RePEc:arx:papers:1611.06407
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1611.06407
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gilles Teyssière & Alan P. Kirman (ed.), 2007. "Long Memory in Economics," Springer Books, Springer, number 978-3-540-34625-8, March.
    2. Robert J. Shiller, 2015. "Irrational Exuberance," Economics Books, Princeton University Press, edition 3, number 10421.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gontis, V. & Kononovicius, A., 2017. "Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 266-272.
    2. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
    3. Vygintas Gontis & Aleksejus Kononovicius, 2017. "The consentaneous model of the financial markets exhibiting spurious nature of long-range memory," Papers 1712.05121, arXiv.org, revised Feb 2018.
    4. Gontis, V. & Kononovicius, A., 2018. "The consentaneous model of the financial markets exhibiting spurious nature of long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1075-1083.
    5. V. Gontis & A. Kononovicius, 2017. "Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets," Papers 1701.01255, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schmitt, Noemi & Westerhoff, Frank, 2017. "On the bimodality of the distribution of the S&P 500's distortion: Empirical evidence and theoretical explanations," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 34-53.
    2. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
    3. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
    4. Daisuke Ikeda & Toan Phan & Timothy Sablik, 2020. "Asset Bubbles and Global Imbalances," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, vol. 20, pages 1-4, January.
    5. Joshua Schwartzstein & Adi Sunderam, 2021. "Using Models to Persuade," American Economic Review, American Economic Association, vol. 111(1), pages 276-323, January.
    6. Scheffknecht, Lukas & Geiger, Felix, 2011. "A behavioral macroeconomic model with endogenous boom-bust cycles and leverage dynamcis," FZID Discussion Papers 37-2011, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    7. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    8. Maysam Khodayari Gharanchaei & Reza Babazadeh, 2024. "Crisis Alpha: A High-Performance Trading Algorithm Tested in Market Downturns," Papers 2409.14510, arXiv.org.
    9. Taner Akan & Tim Solle, 2022. "Do macroeconomic and financial governance matter? Evidence from Germany, 1950–2019," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(4), pages 993-1045, October.
    10. Alan Randall, 2022. "Driving with Eyes on the Rear-View Mirror—Why Weak Sustainability Is Not Enough," Sustainability, MDPI, vol. 14(16), pages 1-13, August.
    11. Wang, Danxia, 2024. "Beyond active share: Boosting fund performance through common holdings with same-benchmark mutual funds," International Review of Financial Analysis, Elsevier, vol. 92(C).
    12. Anufriev, Mikhail & Panchenko, Valentyn, 2009. "Asset prices, traders' behavior and market design," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1073-1090, May.
    13. Kei Nanamiya, 2011. "The Wavelet-based Estimation for Long Memory Signal Plus Noise Models," Global COE Hi-Stat Discussion Paper Series gd11-210, Institute of Economic Research, Hitotsubashi University.
    14. Fernández-Villaverde, Jesús & Levintal, Oren, 2024. "The Distributional Effects of Asset Returns," CEPR Discussion Papers 18855, C.E.P.R. Discussion Papers.
    15. Staccioli, Jacopo & Napoletano, Mauro, 2021. "An agent-based model of intra-day financial markets dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 331-348.
    16. Franke, Reiner, 2008. "Artificial Long Memory Effects in Two Agend-Based Asset Pricing Models," Economics Working Papers 2008-15, Christian-Albrechts-University of Kiel, Department of Economics.
    17. Cortés, Kristle & Duchin, Ran & Sosyura, Denis, 2016. "Clouded judgment: The role of sentiment in credit origination," Journal of Financial Economics, Elsevier, vol. 121(2), pages 392-413.
    18. Ricardo Delao & Sean Myers, 2021. "Subjective Cash Flow and Discount Rate Expectations," Journal of Finance, American Finance Association, vol. 76(3), pages 1339-1387, June.
    19. Carlos Garriga & Athena Tsouderou & Pedro Gete, 2019. "Housing Dynamics without Homeowners. The Role of I," 2019 Meeting Papers 1407, Society for Economic Dynamics.
    20. Corgnet, Brice & DeSantis, Mark & Porter, David, 2021. "Information aggregation and the cognitive make-up of market participants," European Economic Review, Elsevier, vol. 133(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1611.06407. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.