High-Frequency Trading around Large Institutional Orders
Author
Suggested Citation
Download full text from publisher
Other versions of this item:
- 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.
References listed on IDEAS
- Stijn Van Nieuwerburgh & Laura Veldkamp, 2009.
"Information Immobility and the Home Bias Puzzle,"
Journal of Finance, American Finance Association, vol. 64(3), pages 1187-1215, June.
- Laura Veldkamp & Stijn Van Nieuwerburgh, 2004. "Information Immobility and the Home Bias Puzzle," Working Papers 04-32, New York University, Leonard N. Stern School of Business, Department of Economics.
- Stijn Van Nieuwerburgh & Laura Veldkamp, 2007. "Information Immobility and the Home Bias Puzzle," NBER Working Papers 13366, National Bureau of Economic Research, Inc.
- Laura Veldkamp & Stijn Van Nieuwerburgh, 2005. "Information Immobility and the Home Bias Puzzle," 2005 Meeting Papers 78, Society for Economic Dynamics.
- Easley, David & de Prado, Marcos Lopez & O'Hara, Maureen, 2016. "Discerning information from trade data," Journal of Financial Economics, Elsevier, vol. 120(2), pages 269-285.
- Frenkel, Jacob A, 1977. "The Forward Exchange Rate, Expectations, and the Demand for Money: The German Hyperinflation," American Economic Review, American Economic Association, vol. 67(4), pages 653-670, September.
- Glosten, Lawrence R, 1987. "Components of the Bid-Ask Spread and the Statistical Properties of Transaction Prices," Journal of Finance, American Finance Association, vol. 42(5), pages 1293-1307, December.
- Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1996. "Cream-Skimming or Profit-Sharing? The Curious Role of Purchased Order Flow," Journal of Finance, American Finance Association, vol. 51(3), pages 811-833, July.
- Davies, Ryan J. & Kim, Sang Soo, 2009. "Using matched samples to test for differences in trade execution costs," Journal of Financial Markets, Elsevier, vol. 12(2), pages 173-202, May.
- Juhani T. Linnainmaa & Gideon Saar, 2012. "Lack of Anonymity and the Inference from Order Flow," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1414-1456.
- Anand, Amber & Irvine, Paul & Puckett, Andy & Venkataraman, Kumar, 2013. "Institutional trading and stock resiliency: Evidence from the 2007–2009 financial crisis," Journal of Financial Economics, Elsevier, vol. 108(3), pages 773-797.
- Menkveld, Albert J., 2013.
"High frequency trading and the new market makers,"
Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
- Albert J. Menkveld, 2011. "High Frequency Trading and the New-Market Makers," Tinbergen Institute Discussion Papers 11-076/2/DSF21, Tinbergen Institute, revised 15 Aug 2011.
- Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
- 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.
- Brogaard, Jonathan & Hendershott, Terrence & Riordan, Ryan, 2013. "High frequency trading and price discovery," Working Paper Series 1602, European Central Bank.
- Vincent van Kervel, 2015. "Competition for Order Flow with Fast and Slow Traders," The Review of Financial Studies, Society for Financial Studies, vol. 28(7), pages 2094-2127.
- 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.
- Hendershott, Terrence & Jones, Charles M. & Menkveld, Albert J., 2008. "Does algorithmic trading improve liquidity?," CFS Working Paper Series 2008/41, Center for Financial Studies (CFS).
- Bruno Biais & Pierre Hillion & Chester Spatt, 1999. "Price Discovery and Learning during the Preopening Period in the Paris Bourse," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1218-1248, December.
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.- Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
- Michael Goldstein & Amy Kwan & Richard Philip, 2023. "High-Frequency Trading Strategies," Management Science, INFORMS, vol. 69(8), pages 4413-4434, August.
- Kang, Jongho & Kang, Jangkoo & Kwon, Kyung Yoon, 2022. "Market versus limit orders of speculative high-frequency traders and price discovery," Research in International Business and Finance, Elsevier, vol. 63(C).
- Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023.
"When is the order-to-trade ratio fee effective?,"
Journal of Financial Markets, Elsevier, vol. 62(C).
- NIdhi Aggarwal & Venkatesh Panchapagesan & Susan Thomas, 2022. "When is the order-to-trade ratio fee effective?," Working Papers 11, xKDR.
- Cécile Bastidon, 2017.
"Stock markets fragmentation, volatility and final investors,"
Annals of Finance, Springer, vol. 13(4), pages 435-451, November.
- Cécile Bastidon, 2017. "Stock markets fragmentation, volatility and final investors," Post-Print hal-03318507, HAL.
- Friederich, Sylvain & Payne, Richard, 2015. "Order-to-trade ratios and market liquidity," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 214-223.
- 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".
- 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.
- 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).
- Jagannathan, Ravi & Pelizzon, Loriana & Schaumburg, Ernst & Getmansky Sherman, Mila & Yuferova, Darya, 2021. "Recovery from fast crashes: Role of mutual funds," SAFE Working Paper Series 227, Leibniz Institute for Financial Research SAFE, revised 2021.
- 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).
- Hans Degryse & Rudy de Winne & Carole Gresse & Richard Payne, 2018.
"Cross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidity,"
Post-Print
hal-01947824, HAL.
- Hans Degryse & Rudy de Winne & Carole Gresse & Richard Payne, 2021. "Cross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidity," Working Papers hal-03338259, HAL.
- Degryse, Hans & De Winne, Rudy & Gresse, Carole & Payne, Richard, 2019. "Cross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidity," LIDAM Discussion Papers LFIN 2019001, Université catholique de Louvain, Louvain Finance (LFIN).
- Benjamin Clapham & Martin Haferkorn & Kai Zimmermann, 2023. "The Impact of High-Frequency Trading on Modern Securities Markets," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(1), pages 7-24, February.
- Watson, Ethan D. & Woods, Donovan, 2022. "Exchange introduction and market competition: The entrance of MEMX and MIAX," Global Finance Journal, Elsevier, vol. 54(C).
- Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Lescourret, Laurence & Moinas, Sophie, 2014.
"Liquidity Supply across Multiple Trading Venues,"
TSE Working Papers
14-533, Toulouse School of Economics (TSE), revised Mar 2015.
- Lescourret, Laurence & Moinas, Sophie, 2015. "Liquidity Supply across Multiple Trading Venues," ESSEC Working Papers WP1505, ESSEC Research Center, ESSEC Business School.
- Laurence Lescourret & Sophie Moinas, 2015. "Liquidity Supply across Multiple Trading Venues," Working Papers hal-01137813, HAL.
- Foucault, Thierry & Moinas, Sophie, 2018. "Is Trading Fast Dangerous?," TSE Working Papers 18-881, Toulouse School of Economics (TSE).
- Rzayev, Khaladdin & Ibikunle, Gbenga & Steffen, Tom, 2023. "The market quality implications of speed in cross-platform trading: evidence from Frankfurt-London microwave," LSE Research Online Documents on Economics 119989, London School of Economics and Political Science, LSE Library.
- Rzayev, Khaladdin & Ibikunle, Gbenga & Steffen, Tom, 2023. "The market quality implications of speed in cross-platform trading: Evidence from Frankfurt-London microwave," Journal of Financial Markets, Elsevier, vol. 66(C).
- Benos, Evangelos & Sagade, Satchit, 2016. "Price discovery and the cross-section of high-frequency trading," Journal of Financial Markets, Elsevier, vol. 30(C), pages 54-77.
- Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
More about this item
Keywords
High-frequency traders; institutional investors; trading patterns; transaction cost;All these keywords.
JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
NEP fields
This paper has been announced in the following NEP Reports:- NEP-FMK-2017-10-08 (Financial Markets)
- NEP-MST-2017-10-08 (Market Microstructure)
Statistics
Access and download statisticsCorrections
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:tin:wpaper:20170092. 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: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.