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Agent-based model with asymmetric trading and herding for complex financial systems

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  • Jun-jie Chen
  • Bo Zheng
  • Lei Tan

Abstract

Background: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results: With the model parameters determined for six representative stock-market indices in the world respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions: We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.

Suggested Citation

  • Jun-jie Chen & Bo Zheng & Lei Tan, 2014. "Agent-based model with asymmetric trading and herding for complex financial systems," Papers 1407.5258, arXiv.org.
  • Handle: RePEc:arx:papers:1407.5258
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    1. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 353-384.
    2. Kenneth A. Kim & John R. Nofsinger, 2005. "Institutional Herding, Business Groups, and Economic Regimes: Evidence from Japan," The Journal of Business, University of Chicago Press, vol. 78(1), pages 213-242, January.
    3. Giardina, Irene & Bouchaud, Jean-Philippe & Mézard, Marc, 2001. "Microscopic models for long ranged volatility correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 28-39.
    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. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    6. Ruiz, Esther & Veiga, Helena, 2008. "Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2846-2862, February.
    7. Li, Junye, 2011. "Volatility components, leverage effects, and the return-volatility relations," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1530-1540, June.
    8. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    9. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    10. Andreas Walter & Friedrich Moritz Weber, 2006. "Herding in the German Mutual Fund Industry," European Financial Management, European Financial Management Association, vol. 12(3), pages 375-406, June.
    11. Jaume Masoliver & Josep Perello, 2006. "Multiple time scales and the exponential Ornstein-Uhlenbeck stochastic volatility model," Quantitative Finance, Taylor & Francis Journals, vol. 6(5), pages 423-433.
    12. Hwang, Soosung & Salmon, Mark, 2004. "Market stress and herding," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 585-616, September.
    13. Irene Giardina & Jean-Philippe Bouchaud & Marc Mezard, 2001. "Microscopic models for long ranged volatility correlations," Science & Finance (CFM) working paper archive 500024, Science & Finance, Capital Fund Management.
    14. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 177-210.
    15. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2001. "Stylized facts of financial markets and market crashes in Minority Games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 294(3), pages 514-524.
    16. X. F. Jiang & B. Zheng, 2012. "Anti-correlation and subsector structure in financial systems," Papers 1201.6418, arXiv.org.
    17. Qiu, T. & Zheng, B. & Ren, F. & Trimper, S., 2007. "Statistical properties of German Dax and Chinese indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 387-398.
    18. Natividad Blasco & Pilar Corredor & Sandra Ferreruela, 2012. "Does herding affect volatility? Implications for the Spanish stock market," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 311-327, July.
    19. Park, Beum-Jo, 2011. "Asymmetric herding as a source of asymmetric return volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2657-2665, October.
    20. Yanhui Liu & Parameswaran Gopikrishnan & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1999. "The statistical properties of the volatility of price fluctuations," Papers cond-mat/9903369, arXiv.org, revised Mar 1999.
    21. Marc Potters & Jean-Philippe Bouchaud, 2001. "More stylized facts of financial markets: leverage effect and downside correlations," Science & Finance (CFM) working paper archive 29960, Science & Finance, Capital Fund Management.
    22. Bouchaud, Jean-Philippe & Potters, Marc, 2001. "More stylized facts of financial markets: leverage effect and downside correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 60-70.
    23. Jean-Philippe Bouchaud & Andrew Matacz & Marc Potters, 2001. "The leverage effect in financial markets: retarded volatility and market panic," Science & Finance (CFM) working paper archive 0101120, Science & Finance, Capital Fund Management.
    24. Andrea Buraschi & Paolo Porchia & Fabio Trojani, 2010. "Correlation Risk and Optimal Portfolio Choice," Journal of Finance, American Finance Association, vol. 65(1), pages 393-420, February.
    25. X. F. Jiang & T. T. Chen & B. Zheng, 2013. "Time-reversal asymmetry in financial systems," Papers 1308.0669, arXiv.org.
    26. R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 237-245.
    27. Ahlgren, Peter Toke Heden & Jensen, Mogens H. & Simonsen, Ingve & Donangelo, Raul & Sneppen, Kim, 2007. "Frustration driven stock market dynamics: Leverage effect and asymmetry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 1-4.
    28. Irene Giardina & Jean-Philippe Bouchaud & Marc M'ezard, 2001. "Microscopic Models for Long Ranged Volatility Correlations," Papers cond-mat/0105076, arXiv.org.
    29. Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
    30. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    31. Jiang, X.F. & Chen, T.T. & Zheng, B., 2013. "Time-reversal asymmetry in financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5369-5375.
    32. Giraitis, Liudas & Leipus, Remigijus & Robinson, Peter M. & Surgailis, Donatas, 2004. "LARCH, leverage, and long memory," LSE Research Online Documents on Economics 294, London School of Economics and Political Science, LSE Library.
    33. Tian Qiu & Bo Zheng & Guang Chen, 2010. "Adaptive financial networks with static and dynamic thresholds," Papers 1002.3432, arXiv.org.
    34. Jansen, Dennis W. & Tsai, Chun-Li, 2010. "Monetary policy and stock returns: Financing constraints and asymmetries in bull and bear markets," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 981-990, December.
    35. Haugen, Robert A & Talmor, Eli & Torous, Walter N, 1991. "The Effect of Volatility Changes on the Level of Stock Prices and Subsequent Expected Returns," Journal of Finance, American Finance Association, vol. 46(3), pages 985-1007, July.
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    3. Jun-Jie Chen & Lei Tan & Bo Zheng, 2015. "Agent-based model with multi-level herding for complex financial systems," Papers 1504.01811, arXiv.org.
    4. Chen, Ting-Ting & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2018. "Information driving force and its application in agent-based modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 593-601.
    5. T. Takaishi, 2021. "Power-Law Return-Volatility Cross Correlations of Bitcoin," Papers 2102.08187, arXiv.org.
    6. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Ren, Fei & He, Yun-Xing, 2018. "Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 301-310.

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