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Prices, debt and market structure in an agent-based model of the financial market

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  • Fischer, Thomas
  • Riedler, Jesper

Abstract

We develop an agent-based model in which heterogenous and boundedly rational agents interact by trading a risky asset at an endogenously set price. Agents are endowed with balance sheets comprising the risky asset as well as cash on the asset side and equity capital as well as debt on the liabilities side. The introduction of balance sheets and debt into an agent-based setup is relatively new to the literature and allows us to tackle several research questions that are mostly inaccessible following conventional methodology, especially representative agent models. A number of findings emerge when simulating the model. We find that the empirically observable log-normal distribution of bank balance sheet size naturally emerges and that higher levels of leverage lead to a greater inequality among agents. When further analyzing the relationship between leverage and balance sheets, we observe that decreasing credit frictions result in an increasingly procyclical behavior of leverage, which is typical for investment banks. We show how decreasing credit frictions increase volatility but decrease the number of bankruptcies.
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Suggested Citation

  • Fischer, Thomas & Riedler, Jesper, 2014. "Prices, debt and market structure in an agent-based model of the financial market," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77240, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:77240
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/77240/
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    Cited by:

    1. Alexandru Mandes & Peter Winker, 2017. "Complexity and model comparison in agent based modeling of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 469-506, October.
    2. Riedler, Jesper & Brueckbauer, Frank, 2017. "Evaluating regulation within an artificial financial system: A framework and its application to the liquidity coverage ratio regulation," ZEW Discussion Papers 17-022, ZEW - Leibniz Centre for European Economic Research.
    3. Wolski, Marcin & van de Leur, Michiel, 2016. "Interbank loans, collateral and modern monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 388-416.
    4. Yuri Biondi & Feng Zhou, 2019. "Interbank credit and the money manufacturing process: a systemic perspective on financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 437-468, September.
    5. Fischer, Thomas, 2015. "Market structure and rating strategies in credit rating markets – A dynamic model with matching of heterogeneous bond issuers and rating agencies," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 39-56.
    6. Enrico Cozzoni & Carmine Passavanti & Cristina Ponsiglione & Simonetta Primario & Pierluigi Rippa, 2021. "Interorganizational Collaboration in Innovation Networks: An Agent Based Model for Responsible Research and Innovation in Additive Manufacturing," Sustainability, MDPI, vol. 13(13), pages 1-17, July.
    7. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.
    8. Karen Braun-Munzinger & Zijun Liu & Arthur Turrell, 2016. "An agent-based model of dynamics in corporate bond trading," Bank of England working papers 592, Bank of England.
    9. Gaffeo, Edoardo, 2019. "Leverage and evolving heterogeneous beliefs in a simple agent-based financial market," Finance Research Letters, Elsevier, vol. 29(C), pages 272-279.
    10. Florian Chávez-Juárez, 2017. "On the Role of Agent-based Modeling in the Theory of Development Economics," Review of Development Economics, Wiley Blackwell, vol. 21(3), pages 713-730, August.
    11. Wood, Aaron D. & Mason, Charles F. & Finnoff, David, 2016. "OPEC, the Seven Sisters, and oil market dominance: An evolutionary game theory and agent-based modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 66-78.
    12. Matteo Serri & Guido Caldarelli & Giulio Cimini, 2016. "How the interbank market becomes systemically dangerous: an agent-based network model of financial distress propagation," Papers 1611.04311, arXiv.org.
    13. Schasfoort, Joeri & Stockermans, Christopher, 2017. "Fundamentals unknown: Momentum, mean-reversion and price-to-earnings trading in an artificial stock market," Economics Discussion Papers 2017-63, Kiel Institute for the World Economy (IfW Kiel).
    14. Thomas Ankenbrand & Fabian Kostadinov & Faten Ben Bouheni & Mondher Bellalah, 2020. "Cyclical behaviour of the Swiss real estate market," International Journal of Entrepreneurship and Small Business, Inderscience Enterprises Ltd, vol. 39(1/2), pages 71-99.
    15. Cavalli, Fausto & Naimzada, Ahmad & Pecora, Nicolò & Pireddu, Marina, 2018. "Market sentiment and heterogeneous fundamentalists in an evolutive financial market mode," MPRA Paper 90289, University Library of Munich, Germany.

    More about this item

    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
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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