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Mid-price estimation for European corporate bonds: a particle filtering approach

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  • Olivier Gu'eant
  • Jiang Pu

Abstract

In most illiquid markets, there is no obvious proxy for the market price of an asset. The European corporate bond market is an archetypal example of such an illiquid market where mid-prices can only be estimated with a statistical model. In this OTC market, dealers / market makers only have access, indeed, to partial information about the market. In real time, they know the price associated with their trades on the dealer-to-dealer (D2D) and dealer-to-client (D2C) markets, they know the result of the requests for quotes (RFQ) they answered, and they have access to composite prices (e.g., Bloomberg CBBT). This paper presents a Bayesian method for estimating the mid-price of corporate bonds by using the real-time information available to a dealer. This method relies on recent ideas coming from the particle filtering / sequential Monte-Carlo literature.

Suggested Citation

  • Olivier Gu'eant & Jiang Pu, 2018. "Mid-price estimation for European corporate bonds: a particle filtering approach," Papers 1810.05884, arXiv.org, revised Mar 2019.
  • Handle: RePEc:arx:papers:1810.05884
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    References listed on IDEAS

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    1. Sanford J. Grossman & Merton H. Miller, 1988. "Liquidity and Market Structure," NBER Working Papers 2641, National Bureau of Economic Research, Inc.
    2. Olivier Gu'eant & Charles-Albert Lehalle & Joaquin Fernandez Tapia, 2011. "Dealing with the Inventory Risk. A solution to the market making problem," Papers 1105.3115, arXiv.org, revised Aug 2012.
    3. Olivier Gu'eant & Charles-Albert Lehalle & Joaquin Fernandez Tapia, 2011. "Optimal Portfolio Liquidation with Limit Orders," Papers 1106.3279, arXiv.org, revised Jul 2012.
    4. Jean-David Fermanian & Olivier Guéant & Jiang Pu, 2016. "The behavior of dealers and clients on the European corporate bond market: the case of Multi-Dealer-to-Client platforms," Working Papers hal-01393134, HAL.
    5. Jean-David Fermanian & Olivier Guéant & Jiang Pu, 2016. "The behavior of dealers and clients on the European corporate bond market: the case of Multi-Dealer-to-Client platforms," Working Papers 2016-34, Center for Research in Economics and Statistics.
    6. Grossman, Sanford J & Miller, Merton H, 1988. " Liquidity and Market Structure," Journal of Finance, American Finance Association, vol. 43(3), pages 617-637, July.
    7. Fabien Guilbaud & Huyên Pham, 2013. "Optimal high-frequency trading with limit and market orders," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 79-94, January.
    8. Ho, Thomas S Y & Stoll, Hans R, 1983. "The Dynamics of Dealer Markets under Competition," Journal of Finance, American Finance Association, vol. 38(4), pages 1053-1074, September.
    9. Ho, Thomas & Stoll, Hans R., 1981. "Optimal dealer pricing under transactions and return uncertainty," Journal of Financial Economics, Elsevier, vol. 9(1), pages 47-73, March.
    10. Marco Avellaneda & Sasha Stoikov, 2008. "High-frequency trading in a limit order book," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 217-224.
    11. repec:dau:papers:123456789/7305 is not listed on IDEAS
    12. N. Chopin & P. E. Jacob & O. Papaspiliopoulos, 2013. "SMC-super-2: an efficient algorithm for sequential analysis of state space models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 397-426, June.
    13. Olivier Gu'eant, 2016. "Optimal market making," Papers 1605.01862, arXiv.org, revised May 2017.
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