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Discipline of Business Analytics

A Hidden Markov Process Approach to Information-Based Trading

Dr Jing Zhao, La Trobe University

18th May 2012  11:00 am - Room 498, Merewether Building

This paper proposes a novel approach to information-based trading, incorporating the dynamics and serial correlation of trading activities.  Unlike the existing approaches of sequential trading modeling, it updates the prior belief of information states using newly observed order flows and identifies trading motives in a data-driven manner.  It allows the set of information states to vary across time and companies.  Extensive simulation demonstrates that the proposed approach can generate dynamic daily measures of information-based trading in high accuracy.  Based on a sample of 30 NYSE stocks, we provide evidence of the significant explanatory power of information-based trading on return volatility.