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Average cross-responses in correlated financial markets

Author

Listed:
  • Shanshan Wang

    (Fakultät für Physik, Universität Duisburg-Essen)

  • Rudi Schäfer

    (Fakultät für Physik, Universität Duisburg-Essen)

  • Thomas Guhr

    (Fakultät für Physik, Universität Duisburg-Essen)

Abstract

There are non-vanishing price responses across different stocks in correlated financial markets, reflecting non-Markovian features. We further study this issue by performing different averages, which identify active and passive cross-responses. The two average cross-responses show different characteristic dependences on the time lag. The passive cross-response exhibits a shorter response period with sizeable volatilities, while the corresponding period for the active cross-response is longer. The average cross-responses for a given stock are evaluated either with respect to the whole market or to different sectors. Using the response strength, the influences of individual stocks are identified and discussed. Moreover, the various cross-responses as well as the average cross-responses are compared with the self-responses. In contrast to the short-memory trade sign cross-correlations for each pair of stocks, the sign cross-correlations averaged over different pairs of stocks show long memory.

Suggested Citation

  • Shanshan Wang & Rudi Schäfer & Thomas Guhr, 2016. "Average cross-responses in correlated financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(9), pages 1-13, September.
    • Handle: RePEc:spr:eurphb:v:89:y:2016:i:9:d:10.1140_epjb_e2016-70137-0
    DOI: 10.1140/epjb/e2016-70137-0
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    References listed on IDEAS

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    1. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, September.
    2. Hens, Thorsten & Schenk-Hoppe, Klaus Reiner (ed.), 2009. "Handbook of Financial Markets: Dynamics and Evolution," Elsevier Monographs, Elsevier, edition 1, number 9780123742582.
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    Cited by:

    1. Juan C. Henao-Londono & Sebastian M. Krause & Thomas Guhr, 2021. "Price response functions and spread impact in correlated financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(4), pages 1-20, April.
    2. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2020. "Comparing the market microstructure between two South African exchanges," Papers 2011.04367, arXiv.org.
    3. Luis Carlos Garc'ia del Molino & Iacopo Mastromatteo & Michael Benzaquen & Jean-Philippe Bouchaud, 2018. "The Multivariate Kyle model: More is different," Papers 1806.07791, arXiv.org, revised Dec 2018.
    4. Henao-Londono, Juan C. & Guhr, Thomas, 2022. "Foreign exchange markets: Price response and spread impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    5. L. C. Garcia Del Molino & I. Mastromatteo & Michael Benzaquen & J.-P. Bouchaud, 2019. "The Multivariate Kyle model: More is different," Working Papers hal-02323433, HAL.
    6. Juan Camilo Henao Londono & Thomas Guhr, 2021. "Foreign exchange markets: price response and spread impact," Papers 2104.09309, arXiv.org, revised Jul 2021.
    7. Stephan Grimm & Thomas Guhr, 2018. "How spread changes affect the order book: Comparing the price responses of order deletions and placements to trades," Papers 1812.09067, arXiv.org.
    8. Rama Cont & Mihai Cucuringu & Chao Zhang, 2021. "Cross-Impact of Order Flow Imbalance in Equity Markets," Papers 2112.13213, arXiv.org, revised Jun 2023.
    9. Wang, Shanshan & Schreckenberg, Michael & Guhr, Thomas, 2023. "Response functions as a new concept to study local dynamics in traffic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).

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