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The endogenous dynamics of markets: price impact and feedback loops

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  • Jean-Philippe Bouchaud

    (CFM)

Abstract

We review the evidence that the erratic dynamics of markets is to a large extent of endogenous origin, i.e. determined by the trading activity itself and not due to the rational processing of exogenous news. In order to understand why and how prices move, the joint fluctuations of order flow and liquidity - and the way these impact prices - become the key ingredients. Impact is necessary for private information to be reflected in prices, but by the same token, random fluctuations in order flow necessarily contribute to the volatility of markets. Our thesis is that the latter contribution is in fact dominant, resulting in a decoupling between prices and fundamental values, at least on short to medium time scales. We argue that markets operate in a regime of vanishing revealed liquidity, but large latent liquidity, which would explain their hyper-sensitivity to fluctuations. More precisely, we identify a dangerous feedback loop between bid-ask spread and volatility that may lead to micro-liquidity crises and price jumps. We discuss several other unstable feedback loops that should be relevant to account for market crises: imitation, unwarranted quantitative models, pro-cyclical regulation, etc.

Suggested Citation

  • Jean-Philippe Bouchaud, 2010. "The endogenous dynamics of markets: price impact and feedback loops," Papers 1009.2928, arXiv.org.
  • Handle: RePEc:arx:papers:1009.2928
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    Citations

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    Cited by:

    1. Sami Al-Suwailem, 2012. "Complexity and Endogenous Instability," ASSRU Discussion Papers 1203, ASSRU - Algorithmic Social Science Research Unit.
    2. Heckens, Anton J. & Guhr, Thomas, 2022. "New collectivity measures for financial covariances and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    3. Shanshan Wang, 2017. "Trading strategies for stock pairs regarding to the cross-impact cost," Papers 1701.03098, arXiv.org, revised Jul 2017.
    4. Leopoldo S'anchez-Cant'u & Carlos Arturo Soto-Campos & Andriy Kryvko, 2016. "Evidence of Self-Organization in Time Series of Capital Markets," Papers 1604.03996, arXiv.org, revised Mar 2017.
    5. Mei-Ling Cai & Zhang-HangJian Chen & Sai-Ping Li & Xiong Xiong & Wei Zhang & Ming-Yuan Yang & Fei Ren, 2022. "New volatility evolution model after extreme events," Papers 2201.03213, arXiv.org.
    6. Romain Bocher, 2022. "The Intersubjective Markets Hypothesis," Journal of Interdisciplinary Economics, , vol. 34(1), pages 35-50, January.
    7. Jake J. Xia, 2016. "A Model of Synchronization for Self-Organized Crowding Behavior," Papers 1612.01132, arXiv.org.
    8. Pablo Su'arez-Garc'ia & David G'omez-Ullate, 2013. "Multifractality and long memory of a financial index," Papers 1306.0490, arXiv.org.
    9. Romain Bocher, 2023. "Causal Entropic Forces, Narratives and Self-organisation of Capital Markets," Journal of Interdisciplinary Economics, , vol. 35(2), pages 172-190, July.
    10. Zhong, Tao & Peng, Qinke & Wang, Xiao & Zhang, Jing, 2016. "Novel indexes based on network structure to indicate financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 583-594.
    11. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
    12. Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
    13. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "Non-parametric Estimation of Quadratic Hawkes Processes for Order Book Events," Working Papers hal-02998555, HAL.
    14. Al-Suwailem, Sami, 2014. "Complexity and endogenous instability," Research in International Business and Finance, Elsevier, vol. 30(C), pages 393-410.
    15. Zouhaier Dhifaoui, 2022. "Determinism and Non-linear Behaviour of Log-return and Conditional Volatility: Empirical Analysis for 26 Stock Markets," South Asian Journal of Macroeconomics and Public Finance, , vol. 11(1), pages 69-94, June.
    16. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "Non-parametric Estimation of Quadratic Hawkes Processes for Order Book Events," Papers 2005.05730, arXiv.org.
    17. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2021. "Non-parametric Estimation of Quadratic Hawkes Processes for Order Book Events," Post-Print hal-02998555, HAL.
    18. Cai, Mei-Ling & Chen, Zhang-HangJian & Li, Sai-Ping & Xiong, Xiong & Zhang, Wei & Yang, Ming-Yuan & Ren, Fei, 2022. "New volatility evolution model after extreme events," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    19. Fabio Caccioli & Jean-Philippe Bouchaud & J. Doyne Farmer, 2012. "A proposal for impact-adjusted valuation: Critical leverage and execution risk," Papers 1204.0922, arXiv.org, revised Aug 2012.
    20. Lublóy, Ágnes & Gyarmati, Ákos & Váradi, Kata, 2012. "Virtuális árhatás a Budapesti Értéktőzsdén [Virtual price effects on the Budapest stock exchange]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 508-539.

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