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A Competing Risk Analysis of Executions and Cancellations in a Limit Order Market

Author

Listed:
  • Bidisha Chakrabarty

    () (Saint Louis University)

  • Zhaohui Han

    () (Financial Engineering Group, ITG Inc.)

  • Konstantin Tyurin

    () (Indiana University Bloomington)

  • Xiaoyong Zheng

    () (North Carolina State University)

Abstract

The competing risks technique is applied to the analysis of times to execution and cancellation of limit orders submitted on an electronic trading platform. Time-to-execution is found to be more sensitive to the limit price variation than time-to-cancellation, even though it is less sensitive to the limit order size. More importantly, investors who aim to reduce the expected time-to-execution for their limit orders without inducing any significant increase in the risk of subsequent cancellation should submit their orders when the market depth is smaller on the side of their orders or when the market depth is greater on the opposite side of their orders. We also provide a new diagnostic plots method for evaluating the goodness-of-fit of different competing risks models.

Suggested Citation

  • Bidisha Chakrabarty & Zhaohui Han & Konstantin Tyurin & Xiaoyong Zheng, 2006. "A Competing Risk Analysis of Executions and Cancellations in a Limit Order Market," Caepr Working Papers 2006-015, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  • Handle: RePEc:inu:caeprp:2006015
    as

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    File URL: http://www.iub.edu/~caepr/RePEc/PDF/2006/CAEPR2006-015.pdf
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    References listed on IDEAS

    as
    1. Lo, Andrew W. & MacKinlay, A. Craig & Zhang, June, 2002. "Econometric models of limit-order executions," Journal of Financial Economics, Elsevier, vol. 65(1), pages 31-71, July.
    2. Chung, Kee H. & Van Ness, Bonnie F. & Van Ness, Robert A., 1999. "Limit orders and the bid-ask spread," Journal of Financial Economics, Elsevier, vol. 53(2), pages 255-287, August.
    3. McCall, Brian P, 1996. "Unemployment Insurance Rules, Joblessness, and Part-Time Work," Econometrica, Econometric Society, vol. 64(3), pages 647-682, May.
    4. Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460 Elsevier.
    5. Mark Yuying An, 2004. "Likelihood-Based Estimation of a Proportional-Hazard, Competing- Risk Model with Grouped Duration Data," Urban/Regional 0407013, EconWPA.
    6. Lawrence F. Katz, 1986. "Layoffs, Recall and the Duration of Unemployment," NBER Working Papers 1825, National Bureau of Economic Research, Inc.
    7. Peterson, Mark & Sirri, Erik, 2002. "Order Submission Strategy and the Curious Case of Marketable Limit Orders," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(02), pages 221-241, June.
    8. Kee H. Chung & Bonnie F. Van Ness & Robert A. Van Ness, 2004. "Trading Costs And Quote Clustering On The Nyse And Nasdaq After Decimalization," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 27(3), pages 309-328.
    9. Rosholm, Michael & Svarer, Michael, 2001. "Structurally dependent competing risks," Economics Letters, Elsevier, vol. 73(2), pages 169-173, November.
    10. Michael J. Barclay, 2003. "Price Discovery and Trading After Hours," Review of Financial Studies, Society for Financial Studies, vol. 16(4), pages 1041-1073.
    11. Herman J. Bierens & Jose R. Carvalho, 2007. "Semi-nonparametric competing risks analysis of recidivism," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 971-993.
    12. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
    13. Odders-White, Elizabeth R., 2000. "On the occurrence and consequences of inaccurate trade classification," Journal of Financial Markets, Elsevier, vol. 3(3), pages 259-286, August.
    14. Ellul, Andrew & Holden, Craig W. & Jain, Pankaj & Jennings, Robert, 2007. "Order dynamics: Recent evidence from the NYSE," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 636-661, December.
    15. Parlour, Christine A, 1998. "Price Dynamics in Limit Order Markets," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 789-816.
    16. Ciochetti, Brian A. & Deng, Yongheng & Lee, Gail & Shilling, James D. & Yao, Rui, 2003. "A Proportional Hazards Model of Commercial Mortgage Default with Originator Bias," The Journal of Real Estate Finance and Economics, Springer, vol. 27(1), pages 5-23, July.
    17. Robert Battalio & Jason Greene & Brian Hatch, 2002. "Does the Limit Order Routing Decision Matter?," Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 159-194, March.
    18. 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.
    19. Sugato Chakravarty & Robert A. Wood & Robert A. Van Ness, 2004. "Decimals And Liquidity: A Study Of The Nyse," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 27(1), pages 75-94.
    20. Nikolaus Hautsch, 1999. "Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions," Finance 9904002, EconWPA.
    21. Sueyoshi, Glenn T., 1992. "Semiparametric proportional hazards estimation of competing risks models with time-varying covariates," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 25-58.
    22. Ranaldo, Angelo, 2004. "Order aggressiveness in limit order book markets," Journal of Financial Markets, Elsevier, vol. 7(1), pages 53-74, January.
    23. Bessembinder, Hendrik, 2003. "Trade Execution Costs and Market Quality after Decimalization," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(04), pages 747-777, December.
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    Citations

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    Cited by:

    1. Efstathios Panayi & Gareth Peters, 2014. "Survival Models for the Duration of Bid-Ask Spread Deviations," Papers 1406.5487, arXiv.org.
    2. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 22, June.
    3. Rose, Annica, 2014. "The informational effect and market quality impact of upstairs trading and fleeting orders on the Australian Securities Exchange," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 171-184.
    4. Yamamoto, Ryuichi, 2014. "An empirical analysis of non-execution and picking-off risks on the Tokyo Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 369-383.
    5. Zoltan Eisler & Janos Kertesz & Fabrizio Lillo & Rosario Mantegna, 2009. "Diffusive behavior and the modeling of characteristic times in limit order executions," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 547-563.
    6. Roberto Pascual & David Veredas, 2009. "What pieces of limit order book information matter in explaining order choice by patient and impatient traders?," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 527-545.
    7. repec:kap:rqfnac:v:49:y:2017:i:4:d:10.1007_s11156-017-0620-6 is not listed on IDEAS

    More about this item

    Keywords

    Market microstructure; limit order; competing risks; hazard rate; frailty;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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