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Endogenous versus exogenous shocks in systems with memory

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  • Sornette, D
  • Helmstetter, A

Abstract

Systems with long-range persistence and memory are shown to exhibit different precursory as well as recovery patterns in response to shocks of exogenous versus endogenous origins. By endogenous, we envision either fluctuations resulting from an underlying chaotic dynamics or from a stochastic forcing origin which may be external or be an effective coarse-grained description of the microscopic fluctuations. In this scenario, endogenous shocks result from a kind of constructive interference of accumulated fluctuations whose impacts survive longer than the large shocks themselves. As a consequence, the recovery after an endogenous shock is in general slower at early times and can be at long times either slower or faster than after an exogenous perturbation. This offers the tantalizing possibility of distinguishing between an endogenous versus exogenous cause of a given shock, even when there is no “smoking gun”. This could help in investigating the exogenous versus self-organized origins in problems such as the causes of major biological extinctions, of change of weather regimes and of the climate, in tracing the source of social upheaval and wars, and so on. Sornette et al., Volatility fingerprints of large stocks: endogenous versus exogenous, cond-mat/0204626 has already shown how this concept can be applied concretely to differentiate the effects on financial markets of the 11 September 2001 attack or of the coup against Gorbachev on 19 August 1991 (exogenous) from financial crashes such as October 1987 (endogenous).

Suggested Citation

  • Sornette, D & Helmstetter, A, 2003. "Endogenous versus exogenous shocks in systems with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 577-591.
  • Handle: RePEc:eee:phsmap:v:318:y:2003:i:3:p:577-591
    DOI: 10.1016/S0378-4371(02)01371-7
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    Cited by:

    1. 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).
    2. 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.
    3. Sandra Sydnor & Linda Niehm & Yoon Lee & Maria Marshall & Holly Schrank, 2017. "Analysis of post-disaster damage and disruptive impacts on the operating status of small businesses after Hurricane Katrina," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1637-1663, February.
    4. Groot, Robert D., 2005. "Lévy distribution and long correlation times in supermarket sales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 501-514.
    5. Xu, Hai-Chuan & Zhang, Wei & Liu, Yi-Fang, 2014. "Short-term market reaction after trading halts in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 103-111.
    6. Juan V Escobar & Didier Sornette, 2015. "Dynamical Signatures of Collective Quality Grading in a Social Activity: Attendance to Motion Pictures," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-15, January.
    7. Pedro Ramaciotti Morales & Jean-Philippe Cointet & Caterina Froio, 2022. "Posters and protesters," Journal of Computational Social Science, Springer, vol. 5(2), pages 1129-1157, November.
    8. Fry, John, 2012. "Exogenous and endogenous crashes as phase transitions in complex financial systems," MPRA Paper 36202, University Library of Munich, Germany.
    9. Yuri Biondi & Simone Righi, 2015. "Much ado about making money:The impact of disclosure, news and rumors over the formation of security market prices over time," Department of Economics 0075, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    10. Marcel Ausloos, 2014. "A biased view of a few possible components when reflecting on the present decade financial and economic crisis," Papers 1412.0127, arXiv.org.
    11. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    12. Yuri Biondi & Simone Righi, 2020. "Much ado about making money: the impact of disclosure, news and rumors on the formation of security market prices over time," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 333-362, April.
    13. Sornette, Didier & Zhou, Wei-Xing, 2006. "Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 704-726.
    14. John Fry & McMillan David, 2015. "Stochastic modelling for financial bubbles and policy," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1002152-100, December.
    15. John Fry, 2014. "Bubbles, shocks and elementary technical trading strategies," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(1), pages 1-13, January.
    16. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    17. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    18. Hai-Chuan Xu & Wei Zhang & Yi-Fang Liu, 2013. "Short-term Market Reaction after Trading Halts in Chinese Stock Market," Papers 1309.1138, arXiv.org, revised Jun 2014.
    19. Marcel Ausloos, 2013. "Econophysics: Comments on a Few Applications, Successes, Methods and Models," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 101-115, July.
    20. Tanya Araujo & Francisco Louca, 2007. "The geometry of crashes. A measure of the dynamics of stock market crises," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 63-74.
    21. R. D. Groot, 2004. "Levy distribution and long correlation times in supermarket sales," Papers cond-mat/0412163, arXiv.org.
    22. Klimek, Peter & Bayer, Werner & Thurner, Stefan, 2011. "The blogosphere as an excitable social medium: Richter’s and Omori’s Law in media coverage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3870-3875.
    23. Miśkiewicz, Janusz, 2012. "Economy with the time delay of information flow—The stock market case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1388-1394.

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