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A New Spread Estimator

Author

Listed:
  • Michael Bleaney
  • Zhiyong Li

Abstract

A new estimator of bid-ask spreads is presented. When the trade direction is known, any estimate of the spread is associated with a unique series of conjectural mid-prices derived by adjusting the observed transaction price by half the estimated spread. It is shown that the covariance of successive conjectural midprice returns is maximised (or least negative) when the estimated spread is equal to the true spread. A search procedure to maximise this covariance may therefore be used to estimate the true spread. The performance of this estimator under various conditions is examined both theoretically and with Monte Carlo simulations. The simulations confirm the theoretical results. The performance of the estimator is good. The final publication (Review of Quantitative Finance and Accounting, 2015) is available at Springer via http://dx.doi.org/10.1007/s11156-015-0499-z Keywords: Bid-ask Spread, Feedback Trading, Estimation JEL codes: G10

Suggested Citation

  • Michael Bleaney & Zhiyong Li, 2014. "A New Spread Estimator," Discussion Papers 14/01, University of Nottingham, School of Economics.
    • Handle: RePEc:not:notecp:14/01
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    Cited by:

    1. Li, Zhiyong & Lambe, Brendan & Adegbite, Emmanuel, 2018. "New bid-ask spread estimators from daily high and low prices," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 69-86.
    2. Qingfu Liu & Qian Luo & Yiuman Tse & Yuchi Xie, 2020. "The market quality of commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1751-1766, November.
    3. Araújo, Gustavo Silva & Barbedo, Claudio Henrique da S. & Vicente, José Valentim M., 2014. "The adverse selection cost component of the spread of Brazilian stocks," Emerging Markets Review, Elsevier, vol. 21(C), pages 21-41.

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    Keywords

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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