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Leverage and evolving heterogeneous beliefs in a simple agent-based financial market

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  • EDOARDO GAFFEO

Abstract

Recent research has acknowledged the crucial role of financial intermediaries’ balance sheet variables – namely, wealth and leverage – in the dynamics of asset prices. In this paper we use a prototypical “small-type†artificial financial market model with heterogeneous interacting traders to pin down how asset prices are affected by the complex interaction between balance sheet constraints and the endogenous evolution of trading rules.

Suggested Citation

  • Edoardo Gaffeo, 2018. "Leverage and evolving heterogeneous beliefs in a simple agent-based financial market," DEM Working Papers 2018/03, Department of Economics and Management.
  • Handle: RePEc:trn:utwprg:2018/03
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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Adrian, Tobias & Shin, Hyun Song, 2010. "Liquidity and leverage," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 418-437, July.
    3. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. Aymanns, Christoph & Caccioli, Fabio & Farmer, J. Doyne & Tan, Vincent W.C., 2016. "Taming the Basel leverage cycle," Journal of Financial Stability, Elsevier, vol. 27(C), pages 263-277.
    5. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    6. Stefan Thurner & J. Doyne Farmer & John Geanakoplos, 2012. "Leverage causes fat tails and clustered volatility," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 695-707, February.
    7. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    8. Westerhoff, Frank H. & Dieci, Roberto, 2006. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 293-322, February.
    9. Hens, Thorsten & Schenk-Hoppe, Klaus Reiner (ed.), 2009. "Handbook of Financial Markets: Dynamics and Evolution," Elsevier Monographs, Elsevier, edition 1, number 9780123742582.
    10. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    11. Daniel Fricke & Thomas Lux, 2015. "The effects of a financial transaction tax in an artificial financial market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 119-150, April.
    12. Arvind Krishnamurthy, 2010. "Amplification Mechanisms in Liquidity Crises," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 1-30, July.
    13. Fischer, Thomas & Riedler, Jesper, 2014. "Prices, debt and market structure in an agent-based model of the financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 95-120.
    14. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    15. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    16. John Geanakoplos, 2010. "The Leverage Cycle," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 1-65, National Bureau of Economic Research, Inc.
    17. Rama Cont, 2007. "Volatility Clustering in Financial Markets: Empirical Facts and Agent-Based Models," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 289-309, Springer.
    18. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    19. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    20. Colander,David (ed.), 2006. "Post Walrasian Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521865487, September.
    21. Gilles Teyssière & Alan P. Kirman (ed.), 2007. "Long Memory in Economics," Springer Books, Springer, number 978-3-540-34625-8, December.
    22. John Geanakoplos, 2009. "The Leverage Cycle," Cowles Foundation Discussion Papers 1715, Cowles Foundation for Research in Economics, Yale University.
    23. Chen, Haiwei, 2016. "A Tobin tax only on sellers," Finance Research Letters, Elsevier, vol. 19(C), pages 83-89.
    24. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    25. John Geanakoplos, 2009. "The Leverage Cycle," Cowles Foundation Discussion Papers 1715R, Cowles Foundation for Research in Economics, Yale University, revised Jan 2010.
    26. Shin, Hyun Song, 2010. "Risk and Liquidity," OUP Catalogue, Oxford University Press, number 9780199546367.
    27. Colander,David (ed.), 2006. "Post Walrasian Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521684200, September.
    28. Friedman, Daniel & Abraham, Ralph, 2009. "Bubbles and crashes: Gradient dynamics in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 922-937, April.
    29. Pruna, Radu T. & Polukarov, Maria & Jennings, Nicholas R., 2018. "Avoiding regret in an agent-based asset pricing model," Finance Research Letters, Elsevier, vol. 24(C), pages 273-277.
    30. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    31. Shimokawa, Tetsuya & Suzuki, Kyoko & Misawa, Tadanobu, 2007. "An agent-based approach to financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 207-225.
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    Cited by:

    1. Roman Mestre, 2021. "A wavelet approach of investing behaviors and their effects on risk exposures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.

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    More about this item

    Keywords

    Agent-based model; Financial markets; Leverage cycle;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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