  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.
