IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v9y2003i4p358-378.html

Liquidity and market makers: a pseudo-experimental analysis with ultrahigh frequency data

Author

Listed:
  • Jose Montalvo

Abstract

An analysis is given of the effect of market makers on liquidity using a transaction-level database. For this purpose, the focus is on a financial market where a change in regulations created explicitly the category of market maker in 1997 and that date is used to construct a pseudo-experiment. In contrast with other studies that use ultrahigh frequency data, the days to be analysed are selected using a statistical procedure to match observations before and after the change in regulation. The propensity score is used to perform the matching. After choosing the days, an estimate of an ordered probit model is made to explain the intraday behaviour of price changes. The coefficient estimates from the ordered probit model are used to calculate a measure of liquidity based on the steepness of the response function of price changes to volume. The results show that liquidity, measured in this way, has not been affected by the introduction of the market makers.

Suggested Citation

  • Jose Montalvo, 2003. "Liquidity and market makers: a pseudo-experimental analysis with ultrahigh frequency data," The European Journal of Finance, Taylor & Francis Journals, vol. 9(4), pages 358-378.
    • Handle: RePEc:taf:eurjfi:v:9:y:2003:i:4:p:358-378
    DOI: 10.1080/1351847021000025795
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/1351847021000025795
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1351847021000025795?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Christie, William G & Harris, Jeffrey H & Schultz, Paul H, 1994. "Why Did NASDAQ Market Makers Stop Avoiding Odd-Eighth Quotes?," Journal of Finance, American Finance Association, vol. 49(5), pages 1841-1860, December.
    2. Christie, William G & Schultz, Paul H, 1994. "Why Do NASDAQ Market Makers Avoid Odd-Eighth Quotes?," Journal of Finance, American Finance Association, vol. 49(5), pages 1813-1840, December.
    3. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    4. Wahal, Sunil, 1997. "Entry, Exit, Market Makers, and the Bid-Ask Spread," The Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 871-901.
    5. Hasabrouck, Joel & Sofianos, George, 1993. "The Trades of Market Makers: An Empirical Analysis of NYSE Specialists," Journal of Finance, American Finance Association, vol. 48(5), pages 1565-1593, December.
    6. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
    7. Gourieroux, C. & Monfort, A. & Trognon, A., 1985. "A General Approach to Serial Correlation," Econometric Theory, Cambridge University Press, vol. 1(3), pages 315-340, December.
    8. John Board & Charles Sutcliffe & Anne Vila, 2000. "Market Maker Performance: The Search for Fair Weather Market Makers," Journal of Financial Services Research, Springer;Western Finance Association, vol. 17(3), pages 259-276, September.
    9. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    10. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June.
    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. Orly Sade & Roy Stein & Zvi Wiener, 2018. "Israeli Treasury Auction Reform," Israel Economic Review, Bank of Israel, vol. 16(1), pages 41-61.
    2. Murphy Jun Jie Lee, 2013. "The Microstructure of Trading Processes on the Singapore Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4, July-Dece.
    3. Murphy Jun Jie Lee, 2013. "The Microstructure of Trading Processes on the Singapore Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2013, January-A.

    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. Plamen Ch Ivanov & Ainslie Yuen & Pandelis Perakakis, 2014. "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    2. Levin, Eric J. & Wright, Robert E., 2004. "Estimating the profit markup component of the bid-ask spread: evidence from the London Stock Exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 1-19, February.
    3. Hiroyuki Moriya, 2017. "Quantized price volatility model for transaction data," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 397-408, December.
    4. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.
    5. Gerhard, Frank & Hess, Dieter & Pohlmeier, Winfried, 1998. "What a Difference a Day Makes: On the Common Market Microstructure of Trading Days," CoFE Discussion Papers 98/01, University of Konstanz, Center of Finance and Econometrics (CoFE).
    6. Bill M. Cai & Charlie X. Cai & Kevin Keasey, 2007. "Influence of cultural factors on price clustering and price resistance in China's stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 47(4), pages 623-641, December.
    7. Bondarenko, Oleg, 2001. "Competing market makers, liquidity provision, and bid-ask spreads," Journal of Financial Markets, Elsevier, vol. 4(3), pages 269-308, June.
    8. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    9. Frank Gerhard & Dieter Hess & Winfried Pohlmeier, 1999. "What a Difference a Day Makes: On the Common Market Microstructure of Trading Days," Finance 9904006, University Library of Munich, Germany.
    10. Li, Jianhua & Xu, Jianxiang, 2023. "Does the introduction of market maker improve market quality? Evidence from China's Sci-Tech innovation board," Finance Research Letters, Elsevier, vol. 55(PA).
    11. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    12. Blau, Benjamin M., 2018. "Does religiosity affect liquidity in financial markets?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 72-83.
    13. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
    14. Ben Sita, Bernard, 2010. "Autocorrelation of the trade process: Evidence from the Helsinki Stock Exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 538-547, November.
    15. Liu, Hong & Wang, Yajun, 2016. "Market making with asymmetric information and inventory risk," Journal of Economic Theory, Elsevier, vol. 163(C), pages 73-109.
    16. William B. English, 2002. "Financial consolidation and monetary policy," Economic Policy Review, Federal Reserve Bank of New York, vol. 8(May), pages 271-284.
    17. Gerhard, Frank & Hautsch, Nikolaus, 2002. "Volatility estimation on the basis of price intensities," Journal of Empirical Finance, Elsevier, vol. 9(1), pages 57-89, January.
    18. Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, University of Reading.
    19. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    20. Alzahrani, Ahmed A. & Gregoriou, Andros & Hudson, Robert, 2013. "Price impact of block trades in the Saudi stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 322-341.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:taf:eurjfi:v:9:y:2003:i:4:p:358-378. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/REJF20 .

    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.