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Swing Pricing for Mutual Funds: Breaking the Feedback Loop Between Fire Sales and Fund Redemptions

Author

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  • Agostino Capponi

    (Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027)

  • Paul Glasserman

    (Columbia Business School, Columbia University, New York, New York 10027)

  • Marko Weber

    (Department of Mathematics, National University of Singapore, Singapore 119076)

Abstract

We develop a model of the feedback between mutual fund outflows and asset illiquidity. Following a market shock, alert investors anticipate the impact on a fund’s net asset value (NAV) of other investors’ redemptions and exit first at favorable prices. This first-mover advantage may lead to fund failure through a cycle of falling prices and increasing redemptions. Our analysis shows that (i) the first-mover advantage introduces a nonlinear dependence between a market shock and the aggregate impact of redemptions on the fund’s NAV; (ii) as a consequence, there is a critical magnitude of the shock beyond which redemptions brings down the fund; (iii) properly designed swing pricing transfers liquidation costs from the fund to redeeming investors and, by removing the nonlinearity stemming from the first-mover advantage, it reduces these costs and prevents fund failure. Achieving these objectives requires a larger swing factor at larger levels of outflows. The swing factor for one fund may also depend on policies followed by other funds.

Suggested Citation

  • Agostino Capponi & Paul Glasserman & Marko Weber, 2020. "Swing Pricing for Mutual Funds: Breaking the Feedback Loop Between Fire Sales and Fund Redemptions," Management Science, INFORMS, vol. 66(8), pages 3581-3602, August.
  • Handle: RePEc:inm:ormnsc:v:66:y:2020:i:8:p:3581-3602
    DOI: 10.1287/mnsc.2019.3353
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    References listed on IDEAS

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    Cited by:

    1. Vladimir Atanasov & John J. Merrick & Philipp Schuster, 2023. "Mismarking in Mutual Funds," Management Science, INFORMS, vol. 69(2), pages 1275-1300, February.
    2. Lillo, Fabrizio & Livieri, Giulia & Marmi, Stefano & Solomko, Anton & Vaienti, Sandro, 2023. "Analysis of bank leverage via dynamical systems and deep neural networks," LSE Research Online Documents on Economics 119917, London School of Economics and Political Science, LSE Library.
    3. Fricke, Daniel & Jank, Stephan & Wilke, Hannes, 2022. "Who creates and who bears flow externalities in mutual funds?," Discussion Papers 41/2022, Deutsche Bundesbank.
    4. Dunhong Jin & Marcin Kacperczyk & Bige Kahraman & Felix Suntheim, 2022. "Swing Pricing and Fragility in Open-End Mutual Funds," The Review of Financial Studies, Society for Financial Studies, vol. 35(1), pages 1-50.
    5. David Aikman & Daniel Beale & Adam Brinley-Codd & Anne-Caroline Hüser & Giovanni Covi & Caterina Lepore, 2023. "Macro-Prudential Stress Test Models: A Survey," IMF Working Papers 2023/173, International Monetary Fund.
    6. Antoine Baena & Thomas Garcia, 2023. "Swing Pricing et dynamique des flux au regard de la crise Covid-19," Working papers 914, Banque de France.
    7. Zhao Li & Kebin Ma, 2022. "Contagious Bank Runs and Committed Liquidity Support," Management Science, INFORMS, vol. 68(12), pages 9152-9174, December.
    8. Stijn Claessens & Ulf Lewrick, 2022. "Open-ended bond funds: Systemic risks and policy implications," Aussenwirtschaft, University of St. Gallen, School of Economics and Political Science, Swiss Institute for International Economics and Applied Economics Research, vol. 72(01), pages 45-62, December.
    9. Thierry Roncalli, 2021. "Liquidity Stress Testing in Asset Management -- Part 3. Managing the Asset-Liability Liquidity Risk," Papers 2110.01302, arXiv.org.

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