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Survival Models for the Duration of Bid-Ask Spread Deviations

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  • Efstathios Panayi
  • Gareth Peters

Abstract

Many commonly used liquidity measures are based on snapshots of the state of the limit order book (LOB) and can thus only provide information about instantaneous liquidity, and not regarding the local liquidity regime. However, trading in the LOB is characterised by many intra-day liquidity shocks, where the LOB generally recovers after a short period of time. In this paper, we capture this dynamic aspect of liquidity using a survival regression framework, where the variable of interest is the duration of the deviations of the spread from a pre-specified level. We explore a large number of model structures using a branch-and-bound subset selection algorithm and illustrate the explanatory performance of our model.

Suggested Citation

  • Efstathios Panayi & Gareth Peters, 2014. "Survival Models for the Duration of Bid-Ask Spread Deviations," Papers 1406.5487, arXiv.org.
  • Handle: RePEc:arx:papers:1406.5487
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    File URL: http://arxiv.org/pdf/1406.5487
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    References listed on IDEAS

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    1. Al-Suhaibani, Mohammad & Kryzanowski, Lawrence, 2000. "An exploratory analysis of the order book, and order flow and execution on the Saudi stock market," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1323-1357, August.
    2. A. Abhyankar & D. Ghosh & E. Levin & R.J. Limmack, 1997. "Bid-ask Spreads, Trading Volume and Volatility: Intra-day Evidence from the London Stock Exchange," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(3), pages 343-362.
    3. Laurent Deville & Fabrice Riva, 2007. "Liquidity and Arbitrage in Options Markets: A Survival Analysis Approach," Review of Finance, European Finance Association, vol. 11(3), pages 497-525.
    4. 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.
    5. Cristian Gatu & Erricos Kontoghiorghes, 2002. "A branch and bound algorithm for computing the best subset regression models," Computing in Economics and Finance 2002 294, Society for Computational Economics.
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