IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/24098.html
   My bibliography  Save this paper

Stock Price Crashes: Role of Slow-Moving Capital

Author

Listed:
  • Mila Getmansky
  • Ravi Jagannathan
  • Loriana Pelizzon
  • Ernst Schaumburg
  • Darya Yuferova

Abstract

We study the role mutual funds play in the recovery from fast intraday crashes based on data from the National Stock Exchange of India for a single large stock. During normal times, trading activity and liquidity provision by mutual funds is negligible compared to other traders at around 4% of overall activity. Nevertheless, for the two intraday marketwide crashes in our sample, price recovery took place only after mutual funds moved in. Market stability may require the presence of well-capitalized standby liquidity providers for recovery from fast crashes.

Suggested Citation

  • Mila Getmansky & Ravi Jagannathan & Loriana Pelizzon & Ernst Schaumburg & Darya Yuferova, 2017. "Stock Price Crashes: Role of Slow-Moving Capital," NBER Working Papers 24098, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24098
    Note: AP
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w24098.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gromb, Denis & Vayanos, Dimitri, 2002. "Equilibrium and welfare in markets with financially constrained arbitrageurs," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 361-407.
    2. Stoll, Hans R, 1978. "The Supply of Dealer Services in Securities Markets," Journal of Finance, American Finance Association, vol. 33(4), pages 1133-1151, September.
    3. Carole Comerton‐Forde & Terrence Hendershott & Charles M. Jones & Pamela C. Moulton & Mark S. Seasholes, 2010. "Time Variation in Liquidity: The Role of Market‐Maker Inventories and Revenues," Journal of Finance, American Finance Association, vol. 65(1), pages 295-331, February.
    4. Zhiguo He & Arvind Krishnamurthy, 2013. "Intermediary Asset Pricing," American Economic Review, American Economic Association, vol. 103(2), pages 732-770, April.
    5. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    6. Scholtus, Martin & van Dijk, Dick & Frijns, Bart, 2014. "Speed, algorithmic trading, and market quality around macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 89-105.
    7. Mark S. Seasholes & Terrence Hendershott, 2007. "Market Maker Inventories and Stock Prices," American Economic Review, American Economic Association, vol. 97(2), pages 210-214, May.
    8. Albert J. Menkveld & Marius A. Zoican, 2017. "Need for Speed? Exchange Latency and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1188-1228.
    9. Lasse Heje Pedersen & Mark Mitchell & Todd Pulvino, 2007. "Slow Moving Capital," American Economic Review, American Economic Association, vol. 97(2), pages 215-220, May.
    10. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    11. Markus K. Brunnermeier & Lasse Heje Pedersen, 2009. "Market Liquidity and Funding Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2201-2238, June.
    12. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    13. Lyons, Richard K., 1995. "Tests of microstructural hypotheses in the foreign exchange market," Journal of Financial Economics, Elsevier, vol. 39(2-3), pages 321-351.
    14. Andersen, Torben G. & Bondarenko, Oleg, 2014. "Reflecting on the VPIN dispute," Journal of Financial Markets, Elsevier, vol. 17(C), pages 53-64.
    15. Thierry Foucault & Roman Kozhan & Wing Wah Tham, 2017. "Toxic Arbitrage," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1053-1094.
    16. Darrell Duffie, 2010. "Presidential Address: Asset Price Dynamics with Slow‐Moving Capital," Journal of Finance, American Finance Association, vol. 65(4), pages 1237-1267, August.
    17. Giovanni Cespa & Thierry Focault, 2011. "Learning from Prices, Liquidity Spillovers, and Market Segmentation," CSEF Working Papers 284, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    18. Lyons, Richard K., 1997. "A simultaneous trade model of the foreign exchange hot potato," Journal of International Economics, Elsevier, vol. 42(3-4), pages 275-298, May.
    19. Vincent Van Kervel & Albert J. Menkveld, 2019. "High‐Frequency Trading around Large Institutional Orders," Journal of Finance, American Finance Association, vol. 74(3), pages 1091-1137, June.
    20. Bige Kahraman & Heather E. Tookes, 2017. "Trader Leverage and Liquidity," Journal of Finance, American Finance Association, vol. 72(4), pages 1567-1610, August.
    21. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    22. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    23. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    24. Oliver Hansch & Narayan Y. Naik & S. Viswanathan, 1998. "Do Inventories Matter in Dealership Markets? Evidence from the London Stock Exchange," Journal of Finance, American Finance Association, vol. 53(5), pages 1623-1656, October.
    25. Venkataraman, Kumar & Waisburd, Andrew C., 2007. "The Value of the Designated Market Maker," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 735-758, September.
    26. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    27. Peter C. Reiss & Ingrid M. Werner, 1998. "Does Risk Sharing Motivate Interdealer Trading?," Journal of Finance, American Finance Association, vol. 53(5), pages 1657-1703, October.
    28. Menkveld, Albert J. & Wang, Ting, 2013. "How do designated market makers create value for small-caps?," Journal of Financial Markets, Elsevier, vol. 16(3), pages 571-603.
    29. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    30. Ho, Thomas S Y & Stoll, Hans R, 1983. "The Dynamics of Dealer Markets under Competition," Journal of Finance, American Finance Association, vol. 38(4), pages 1053-1074, September.
    31. S. Viswanathan & James J. D. Wang, 2004. "Inter-Dealer Trading in Financial Markets," The Journal of Business, University of Chicago Press, vol. 77(4), pages 987-1040, October.
    32. Johnson, Hardy & Van Ness, Bonnie F. & Van Ness, Robert A., 2017. "Are all odd-lots the same? Odd-lot transactions by order submission and trader type," Journal of Banking & Finance, Elsevier, vol. 79(C), pages 1-11.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Amin, Shehryar & Tédongap, Roméo, 2023. "The changing landscape of treasury auctions," Journal of Banking & Finance, Elsevier, vol. 148(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jagannathan, Ravi & Pelizzon, Loriana & Schaumburg, Ernst & Sherman, Mila Getmansky & Yuferova, Darya, 2022. "Recovery from fast crashes: Role of mutual funds," Journal of Financial Markets, Elsevier, vol. 59(PB).
    2. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    3. Bellia, Mario & Pelizzon, Loriana & Subrahmanyam, Marti & Uno, Jun & Yuferova, Darya, 2017. "Coming early to the party," SAFE Working Paper Series 182, Leibniz Institute for Financial Research SAFE.
      • Mario Bellia & Loriana Pelizzon & Marti G. Subrahmanyam & Jun Uno & Darya Yuferova, 2020. "Coming early to the party," Working Papers 2020:11, Department of Economics, University of Venice "Ca' Foscari".
    4. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    5. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    6. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    7. Thierry Foucault & Roman Kozhan & Wing Wah Tham, 2017. "Toxic Arbitrage," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1053-1094.
    8. Hendershott, Terrence & Menkveld, Albert J., 2014. "Price pressures," Journal of Financial Economics, Elsevier, vol. 114(3), pages 405-423.
    9. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    10. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    11. Foucault, Thierry & Moinas, Sophie, 2018. "Is Trading Fast Dangerous?," TSE Working Papers 18-881, Toulouse School of Economics (TSE).
    12. Benos, Evangelos & Žikeš, Filip, 2018. "Funding constraints and liquidity in two-tiered OTC markets," Journal of Financial Markets, Elsevier, vol. 39(C), pages 24-43.
    13. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    14. Dodd, Olga & Frijns, Bart & Indriawan, Ivan & Pascual, Roberto, 2023. "US cross-listing and domestic high-frequency trading: Evidence from Canadian stocks," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 301-320.
    15. Hendershott, Terrence & Seasholes, Mark S., 2014. "Liquidity provision and stock return predictability," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 140-151.
    16. Mark Marner-Hausen, 2022. "Developing a Framework for Real-Time Trading in a Laboratory Financial Market," ECONtribute Discussion Papers Series 172, University of Bonn and University of Cologne, Germany.
    17. Angerer, Martin & Neugebauer, Tibor & Shachat, Jason, 2023. "Arbitrage bots in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 262-278.
    18. Lescourret, Laurence & Moinas, Sophie, 2014. "Liquidity Supply across Multiple Trading Venues," TSE Working Papers 14-533, Toulouse School of Economics (TSE), revised Mar 2015.
    19. Anagnostidis, Panagiotis & Fontaine, Patrice, 2020. "Liquidity commonality and high frequency trading: Evidence from the French stock market," International Review of Financial Analysis, Elsevier, vol. 69(C).
    20. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

    More about this item

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G2 - Financial Economics - - Financial Institutions and Services

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:24098. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.