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Rebuilding the limit order book: sequential Bayesian inference on hidden states |
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| Authors: | Hugh L Christensen Richard E Turner Simon I Hill Simon J Godsill |
| Institution: | 1. Signal Processing and Communications Laboratory, Engineering Department, Cambridge University, Cambridge CB2 1PZ, UK.hlc54@cam.ac.uk;3. Computational and Biological Learning Laboratory, Engineering Department, Cambridge University, Cambridge CB2 1PZ, UK.;4. Signal Processing and Communications Laboratory, Engineering Department, Cambridge University, Cambridge CB2 1PZ, UK. |
| Abstract: | The limit order book of an exchange represents an information store of market participants’ future aims and for many traders the information held in this store is of interest. However, information loss occurs between orders being entered into the exchange and limit order book data being sent out. We present an online algorithm which carries out Bayesian inference to replace information lost at the level of the exchange server and apply our proof of concept algorithm to real historical data from some of the world’s most liquid futures contracts as traded on CME GLOBEX, EUREX and NYSE Liffe exchanges. |
| Keywords: | Bayesian inference Belief propagation Futures trading Quantitative finance Tracking |