IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1407.4512.html
   My bibliography  Save this paper

Exact and asymptotic solutions of the call auction problem

Author

Listed:
  • Ioane Muni Toke

Abstract

The call auction is a widely used trading mechanism, especially during the opening and closing periods of financial markets. In this paper, we study a standard call auction problem where orders are submitted according to Poisson processes, with random prices distributed according to a general distribution, and may be cancelled at any time. We compute the analytical expressions of the distributions of the traded volume, of the lower and upper bounds of the clearing prices, and of the price range of these possible clearing prices of the call auction. Using results from the theory of order statistics and a theorem on the limit of sequences of random variables with independent random indices, we derive the weak limits of all these distributions. In this setting, traded volume and bounds of the clearing prices are found to be asymptotically normal, while the clearing price range is asymptotically exponential. All the parameters of these distributions are explicitly derived as functions of the parameters of the incoming orders' flows.

Suggested Citation

  • Ioane Muni Toke, 2014. "Exact and asymptotic solutions of the call auction problem," Papers 1407.4512, arXiv.org, revised Nov 2014.
  • Handle: RePEc:arx:papers:1407.4512
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1407.4512
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Comerton-Forde, Carole & Rydge, James, 2006. "Call auction algorithm design and market manipulation," Journal of Multinational Financial Management, Elsevier, vol. 16(2), pages 184-198, April.
    2. Eric Smith & J Doyne Farmer & Laszlo Gillemot & Supriya Krishnamurthy, 2003. "Statistical theory of the continuous double auction," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 481-514.
    3. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    4. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 251-256.
    5. Potters, Marc & Bouchaud, Jean-Philippe, 2003. "More statistical properties of order books and price impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 133-140.
    6. Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
    7. Rama Cont & Sasha Stoikov & Rishi Talreja, 2010. "A Stochastic Model for Order Book Dynamics," Operations Research, INFORMS, vol. 58(3), pages 549-563, June.
    8. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. "An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    9. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Science & Finance (CFM) working paper archive 0203511, Science & Finance, Capital Fund Management.
    10. Comerton-Forde, Carole & Rydge, James, 2006. "The influence of call auction algorithm rules on market efficiency," Journal of Financial Markets, Elsevier, vol. 9(2), pages 199-222, May.
    11. Chan, K C & Christie, William G & Schultz, Paul H, 1995. "Market Structure and the Intraday Pattern of Bid-Ask Spreads for NASDAQ Securities," The Journal of Business, University of Chicago Press, vol. 68(1), pages 35-60, January.
    12. G.-F. Gu & W. Chen & W.-X. Zhou, 2007. "Quantifying bid-ask spreads in the Chinese stock market using limit-order book data," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(1), pages 81-87, May.
    13. Frédéric Abergel & Aymen Jedidi, 2013. "A Mathematical Approach To Order Book Modeling," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1-40.
    14. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: I. Empirical facts," Post-Print hal-00621058, HAL.
    15. Mendelson, Haim, 1982. "Market Behavior in a Clearing House," Econometrica, Econometric Society, vol. 50(6), pages 1505-1524, November.
    16. Pagano, Michael S. & Schwartz, Robert A., 2003. "A closing call's impact on market quality at Euronext Paris," Journal of Financial Economics, Elsevier, vol. 68(3), pages 439-484, June.
    17. Domowitz, Ian & Wang, Jianxin, 1994. "Auctions as algorithms : Computerized trade execution and price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 29-60, January.
    18. Frédéric Abergel & Aymen Jedidi, 2013. "A Mathematical Approach to Order Book Modelling," Post-Print hal-00621253, HAL.
    19. Frederic Abergel & Aymen Jedidi, 2010. "A Mathematical Approach to Order Book Modeling," Papers 1010.5136, arXiv.org, revised Mar 2013.
    Full references (including those not matched with items on IDEAS)

    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. Ioane Muni Toke, 2014. "Exact and asymptotic solutions of the call auction problem," Working Papers hal-01061857, HAL.
    2. Ioane Muni Toke, 2015. "Exact and asymptotic solutions of the call auction problem," Post-Print hal-01061857, HAL.
    3. M. Derksen & B. Kleijn & R. de Vilder, 2019. "Clearing price distributions in call auctions," Papers 1904.07583, arXiv.org, revised Nov 2019.
    4. Kyungsub Lee & Byoung Ki Seo, 2021. "Analytic formula for option margin with liquidity costs under dynamic delta hedging," Papers 2103.15302, arXiv.org.
    5. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
    6. Martin D. Gould & Mason A. Porter & Sam D. Howison, 2015. "Quasi-Centralized Limit Order Books," Papers 1502.00680, arXiv.org, revised Oct 2016.
    7. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    8. Mohammad Zare & Omid Naghshineh Arjmand & Erfan Salavati & Adel Mohammadpour, 2021. "An Agent‐Based model for Limit Order Book: Estimation and simulation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1112-1121, January.
    9. Ioane Muni Toke, 2013. "The order book as a queueing system: average depth and influence of the size of limit orders," Papers 1311.5661, arXiv.org.
    10. Ioane Muni Toke, 2015. "Stationary distribution of the volume at the best quote in a Poisson order book model," Papers 1502.03871, arXiv.org.
    11. Ioane Muni Toke, 2017. "Stationary Distribution Of The Volume At The Best Quote In A Poisson Order Book Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-22, September.
    12. Ioane Muni Toke, 2015. "The order book as a queueing system: average depth and influence of the size of limit orders," Post-Print hal-01006410, HAL.
    13. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    14. Rama Cont & Pierre Degond & Xuan Lifan, 2023. "A mathematical framework for modelling order book dynamics," Working Papers hal-03968767, HAL.
    15. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    16. Rama Cont & Pierre Degond & Lifan Xuan, 2023. "A mathematical framework for modelling order book dynamics," Papers 2302.01169, arXiv.org.
    17. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    18. A. O. Glekin & A. Lykov & K. L. Vaninsky, 2014. "On Simulation of Various Effects in Consolidated Order Book," Papers 1402.4150, arXiv.org.
    19. Philippe Bergault & Enzo Cogn'eville, 2024. "Simulating and analyzing a sparse order book: an application to intraday electricity markets," Papers 2410.06839, arXiv.org.

    More about this item

    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:arx:papers:1407.4512. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.