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Dynamic limit order placement strategies: survival analysis with a multiple-spell duration model

  • S.I.: Networks and Risk Management
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Abstract

This study investigates the multiple events that occur in the life of each limit order by utilising a survival analysis methodology with a multiple-spell duration model. The estimates suggest that the hazard rates of limit order event transitions are determined by a number of factors and their impacts depend on whether the initial order event is a limit order submission, partial execution or revision. The differences in estimates across initial order events increase as exchange latency reduces in recent years. Using a multiple-spell duration model to examine the full spectrum of events that occur in the life of a limit order is thus shown to be informative and essential in modelling dynamic limit order placement strategies.

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Notes

  1. Multiple-spell duration models have been applied extensively in examining labour market dynamics. For a survey of different types of duration model, see van den Berg (2001).

  2. Hasbrouck and Saar (2009) report that 93% of submitted limit orders are subsequently cancelled on INET. They show that orders that are cancelled in the system within only 2 s of their submissions account for as much as 37% of limit order placements. Fong and Liu (2010) also report that more than 60% of limit orders are cancelled or revised on the Australian Stock Exchange.

  3. Multiple-spell duration model has been used more widely in biomedical science and labour economics (see Van den Berg 2011 for review).

  4. One might argue that this assumption is not innocuous because arrival rate changes when information arrives. See Engle (2000). In our study, we choose a period where there are a large number of information events (earning announcements), hence arrival rate of order events should be fairly stable during this period.

  5. In these transitions, the order events on the left-hand side are said to be in the origin states and the order events on the right-hand side are said to be in the destination states.

  6. Since duration is inversely related to the transition probability, the interpretation is loosely interchangeable.

  7. The set of explanatory variables are defined in a similar way to those used in Lo et al. (2002).

  8. In labour economics, negative coefficient estimate for the lagged duration dependence variable suggests that workers start reducing their job search intensity if the subsidised job lasts too long. See Van Ours (2004) for further details.

References

  • Ahn, H. J., Bae, K. H., & Chan, K. (2001). Limit orders, depth and volatility: Evidence from the stock exchange of Hong Kong. Journal of Finance, 61, 767–788.

    Article  Google Scholar 

  • Biais, B., Hillion, P., & Spatt, C. (1995). An empirical analysis of the limit order book and the order flow in the Paris Bourse. Journal of Finance, 50, 1655–1689.

    Article  Google Scholar 

  • Bień-Barkowska, K. (2014). Capturing order book dynamics in the interbank EUR/PLN spot market. Emerging Markets Finance and Trade, 50(1), 93–117.

    Article  Google Scholar 

  • Booth, A. L., Francesconi, M., & Frank, J. (2002). Temporary jobs: Stepping stones or dead ends? The Economic Journal, 112, 189–213.

    Article  Google Scholar 

  • Cao, C., Hansch, O., & Wang, X. (2008). Order placement strategies in a pure limit order book market. Journal of Financial Research, 31(2), 113–140.

    Article  Google Scholar 

  • Chan, C. H., & Ma, A. K. (2013). Order-based manipulation: evidence from Hong Kong stock market. Journal of Financial Crime, 21(1), 111–118.

    Article  Google Scholar 

  • Cohen, K. J., Maier, S. F., Schwartz, R. A., & Whitcomb, D. K. (1981). Transaction costs, order placement strategy, and existence of the bid-ask spread. Journal of Political Economy, 89, 287–305.

    Article  Google Scholar 

  • De Graaf-Zijl, M., Van den Berg, G. J., & Heyma, A. (2011). Stepping stones for the unemployed: The effect of temporary jobs on the duration until (regular) work. Journal of Population Economics, 24(1), 107–139.

    Article  Google Scholar 

  • Easley, D., & O’Hara, M. (1992). Time and the process of security price adjustments. Journal of Finance, 47(2), 577–605.

    Article  Google Scholar 

  • Esteve-Perez, S., Requena-Silvente, F., & Pallardo-Lopez, V. J. (2013). The duration of firm-destination export relationships: Evidence from Spain, 1997–2006. Economic Inquiry, 51(1), 159–180.

    Article  Google Scholar 

  • Fong, K., & Liu, W. M. (2010). Limit order revisions. Journal of Banking & Finance, 34, 1873–1885.

    Article  Google Scholar 

  • Foucault, T. (1999). Order flow composition and trading costs in a dynamic limit order market. Journal of Financial Markets, 2(2), 99–134.

    Article  Google Scholar 

  • Foucault, T., Kadan, O., & Kandel, E. (2005). Limit order book as a market for liquidity. The Review of Financial Studies, 18(4), 1171–1217.

    Article  Google Scholar 

  • Gagliarducci, S. (2005). The dynamics of repeated temporary jobs. Labour Economics, 12(4), 429–448.

    Article  Google Scholar 

  • Glosten, L. R. (1994). Is the electronic open limit order book inevitable?. The Journal of Finance, 49(4), 1127–1161.

    Article  Google Scholar 

  • Hall, A., & Hautsch, N. (2006). Order aggressiveness and order book dynamics. Empirical Economics, 30, 973–1005.

    Article  Google Scholar 

  • Harris, L. (1998). Optimal dynamic order submission strategies in some stylized trading problems. Financial Markets, Institutions and Instruments, 7(2), 1–76.

    Article  Google Scholar 

  • Hasbrouck, J., & Saar, G. (2009). Technology and liquidity provision: The blurring of traditional definitions. Journal of Financial Markets, 12, 143–172.

    Article  Google Scholar 

  • Hasbrouck, J., & Saar, G. (2013). Low-latency trading. Journal of Financial Markets, 16, 646–679.

    Article  Google Scholar 

  • Hollifield, B., Miller, R. A., & Sandas, P. (2004). Empirical analysis of limit order markets. Review of Economic Studies, 71, 1027–1063.

    Article  Google Scholar 

  • Kalbfleisch, J. D., & Prentice, R. L. (2011). The statistical analysis of failure time data (Vol. 360). Hoboken: Wiley.

    Google Scholar 

  • Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53, 1315–1335.

    Article  Google Scholar 

  • Lancaster, T. (1979). Econometric methods for the duration of unemployment. Econometrica, 47(4), 939–956.

    Article  Google Scholar 

  • Liu, W.-M. (2009). Monitoring and limit order submission risks. Journal of Financial Markets, 12, 107–141.

    Article  Google Scholar 

  • Lo, A. W., & Farmer, J. D. (1999). Frontiers of finance: Evolution and efficient markets. Proceedings of the National Academy of Sciences, 96(18), 9991–9992.

    Article  Google Scholar 

  • Lo, A. W., MacKinlay, A. C., & Zhang, J. (2002). Econometric models of limit order executions. Journal of Financial Economics, 65, 31–71.

    Article  Google Scholar 

  • Menkhoff, L., & Schmeling, M. (2010). Whose trades convey information? Evidence from a cross-section of traders. Journal of Financial Markets, 13, 101–128.

    Article  Google Scholar 

  • Parlour, C. (1998). Price dynamics in limit order markets. Review of Financial Studies, 11, 789–816.

    Article  Google Scholar 

  • Ranaldo, A. (2004). Order aggressiveness in limit order markets. Journal of Financial Markets, 7, 53–74.

    Article  Google Scholar 

  • Roşu, I. (2009). A dynamic model of the limit order book. The Review of Financial Studies, 22(11), 4601–4641.

    Article  Google Scholar 

  • Sandas, P. (2001). Adverse selection and competitive market making: Empirical evidence from a limit order market. Review of Financial Studies, 14(3), 705–734.

    Article  Google Scholar 

  • The Trade (nd). ASX introduces high-speed trading platform. Retrieved on 20th August, 2016. http://www.thetradenews.com/newsarticle.aspx?id=5322.

  • Tseng, Y. H., & Chen, S. H. (2015). Limit order book transparency and order aggressiveness at the closing call: Lessons from the TWSE 2012 new information disclosure mechanism. Pacific-Basin Finance Journal, 35, 241–272.

    Article  Google Scholar 

  • Van den Berg, G. J. (2001). Duration models: specification, identification and multiple durations. In Handbook of econometrics. (Vol. 5, pp. 3381–3460). Amsterdam: Elsevier.

  • Van Ness, B. F., Van Ness, R. A., & Watson, E. D. (2015). Canceling liquidity. Journal of Financial Research, 38(1), 3–33.

    Article  Google Scholar 

  • Van Ours, J. C. (2004). The locking-in effect of subsidized jobs. Journal of Accounting and Finance, 32, 37–55.

    Google Scholar 

  • Viljoen, T., Westerholm, J., Zheng, H., & Gerace, D. (2015). Fleeting orders and dynamic trading strategies: Evidence from the Australian security stock exchange (ASX). Journal of Accounting and Finance, 15(4), 108.

    Google Scholar 

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Authors and Affiliations

  1. PwC, Ho Chi Minh City, Vietnam

    Anh Tu Le

  2. University of New South Wales (UNSW), Sydney, Australia

    Anh Tu Le & Kingsley Y. Fong

  3. Fulbright University, Ho Chi Minh City, Vietnam

    Thai-Ha Le

  4. IPAG Business School, Paris, France

    Thai-Ha Le

  5. Australian National University, Canberra, Australia

    Wai-Man Liu

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  1. Anh Tu Le
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  2. Thai-Ha Le
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  4. Kingsley Y. Fong
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Correspondence to Thai-Ha Le.

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Le, A.T., Le, TH., Liu, WM. et al. Dynamic limit order placement strategies: survival analysis with a multiple-spell duration model. Ann Oper Res 297, 241–275 (2021). https://doi.org/10.1007/s10479-019-03384-y

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