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An agent-based model of dynamics in corporate bond trading

Author

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  • Braun-Munzinger, Karen

    (Bank of England)

  • Liu, Zijun

    (Bank of England)

  • Turrell, Arthur

    (Bank of England)

Abstract

We construct a heterogeneous agent-based model of the corporate bond market capturing the interaction of market maker behaviour, fund trading strategies, and cash allocation by investors in funds to study feedback effects and the impact of market changes. The model parameters are calibrated against empirical data on US corporate bond trading. Where available, inputs are taken from market data. Others are calibrated through matching statistical features of market returns such as auto-correlations, volatility and fat tails. We use the model to explore the impact of shocks. We find that the sensitivity of the market maker to demand and the degree to which momentum traders are active strongly influence the over and undershooting of yields in response to a shock. This suggests that correlation in funds’ trading strategies can exacerbate extreme price movements and contribute to the procyclicality of financial markets. While the behaviour of investors in funds based on past experience plays a comparatively smaller role in model dynamics, it represents another source of amplification which could be particularly problematic if investors respond to a shock with greater risk aversion. Simple measures to reduce the speed with which investors can redeem investments can reduce the extent of yield dislocation. We also explore the impact of the growth in passive investment, and find that it increases the tail risk of big yield dislocations after shocks, though, on average, volatility may be reduced.

Suggested Citation

  • Braun-Munzinger, Karen & Liu, Zijun & Turrell, Arthur, 2016. "An agent-based model of dynamics in corporate bond trading," Bank of England working papers 592, Bank of England.
  • Handle: RePEc:boe:boeewp:0592
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    References listed on IDEAS

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    1. Aymanns, Christoph & Farmer, J. Doyne, 2015. "The dynamics of the leverage cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 155-179.
    2. Richard Bookstaber & Michael D. Foley & Brian F. Tivnan, 2015. "Market Liquidity and Heterogeneity in the Investor Decision Cycle," Working Papers 15-03, Office of Financial Research, US Department of the Treasury.
    3. 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.
    4. Moneta, Fabio, 2015. "Measuring bond mutual fund performance with portfolio characteristics," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 223-242.
    5. Jimmy Shek & Ilhyock Shim & Hyun Song Shin, 2018. "Investor Redemptions and Fund Manager Sales of Emerging Market Bonds: How Are They Related? [Borrow cheap, buy high? The determinants of leverage and pricing in buyouts]," Review of Finance, European Finance Association, vol. 22(1), pages 207-241.
    6. Ingo Fender & Ulf Lewrick, 2015. "Shifting tides - market liquidity and market-making in fixed income instruments," BIS Quarterly Review, Bank for International Settlements, March.
    7. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    8. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    9. 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.
    10. 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.
    11. 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.
    12. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    13. 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.
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    Cited by:

    1. Marc van Kralingen & Diego Garlaschelli & Karolina Scholtus & Iman van Lelyveld, 2020. "Crowded trades, market clustering, and price instability," Tinbergen Institute Discussion Papers 20-007/II, Tinbergen Institute.
    2. Farmer, J Doyne & Kleinnijenhuis, Alissa M & Nahai-Williamson, Paul & Wetzer, Thom, 2020. "Foundations of system-wide financial stress testing with heterogeneous institutions," Bank of England working papers 861, Bank of England.
    3. Joeri Schasfoort & Antoine Godin & Dirk Bezemer & Alessandro Caiani & Stephen Kinsella, 2017. "Monetary Policy Transmission In A Macroeconomic Agent-Based Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-35, December.
    4. Takanobu Mizuta, 2019. "An agent-based model for designing a financial market that works well," Papers 1906.06000, arXiv.org.
    5. Karvik, Geir-Are & Noss, Joseph & Worlidge, Jack & Beale, Daniel, 2018. "The deeds of speed: an agent-based model of market liquidity and flash episodes," Bank of England working papers 743, Bank of England.
    6. Tae-Sub Yun & Il-Chul Moon, 2020. "Housing Market Agent-Based Simulation with Loan-To-Value and Debt-To-Income," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(4), pages 1-5.
    7. Takanobu Mizuta & Sadayuki Horie, 2019. "Mechanism by which active funds make market efficient investigated with agent-based model," Evolutionary and Institutional Economics Review, Springer, vol. 16(1), pages 43-63, June.
    8. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    9. Bear, Laura, 2020. "Speculation: a political economy of technologies of imagination," LSE Research Online Documents on Economics 103433, London School of Economics and Political Science, LSE Library.
    10. Andrew G. Haldane & Arthur E. Turrell, 2019. "Drawing on different disciplines: macroeconomic agent-based models," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 39-66, March.
    11. Romain Plassard, 2020. "Making a Breach: The Incorporation of Agent-Based Models into the Bank of England's Toolkit," GREDEG Working Papers 2020-30, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    12. Aikman, David & Haldane, Andrew & Hinterschweiger, Marc & Kapadia, Sujit, 2018. "Rethinking financial stability," Bank of England working papers 712, Bank of England.
    13. Rohan Arora & Guillaume Bédard-Pagé & Guillaume Ouellet Leblanc & Ryan Shotlander, 2019. "Bond Funds and Fixed-Income Market Liquidity: A Stress-Testing Approach," Technical Reports 115, Bank of Canada.

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    More about this item

    Keywords

    Agent-based model; corporate bond market; trading strategies;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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