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Mid-Price Estimation for European Corporate Bonds: A Particle Filtering Approach

Author

Listed:
  • Olivier Guéant

    (ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jiang Pu

    (Institut europlace de finance)

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 Guéant & Jiang Pu, 2018. "Mid-Price Estimation for European Corporate Bonds: A Particle Filtering Approach," Post-Print hal-02862823, HAL.
    • Handle: RePEc:hal:journl:hal-02862823
    DOI: 10.1142/S2382626619500059
    as

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