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A switching microstructure model for stock prices

  • Donatien HainautEmail author
  • Stephane Goutte
Article
  • 13 Downloads

Abstract

This article proposes a microstructure model for stock prices in which parameters are modulated by a Markov chain determining the market behaviour. In this approach, called the switching microstructure model (SMM), the stock price is the result of the balance between the supply and the demand for shares. The arrivals of bid and ask orders are represented by two mutually- and self-excited processes. The intensities of these processes converge to a mean reversion level that depends upon the regime of the Markov chain. The first part of this work studies the mathematical properties of the SMM. The second part focuses on the econometric estimation of parameters. For this purpose, we combine a particle filter with a Markov chain Monte Carlo algorithm. Finally, we calibrate the SMM with two and three regimes to daily returns of the S&P 500 and compare them with a non switching model.

Keywords

Hawkes process Switching process Microstructure 

JEL Classifications

C58 G1 

Notes

Acknowledgements

We thank for its support the Chair “Data Analytics and Models for insurance” of BNP Paribas Cardif, hosted by ISFA (Université Claude Bernard, Lyon France). We also thank the two anonymous referees and the editor, Ulrich Horst, for their recommandations.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Statistics, Bio-statistics and Actuarial Science (ISBA)Université Catholique de LouvainLouvain-la-NeuveBelgium
  2. 2.Laboratoire d’Economie Dionysien (LED)Université Paris 8 and Paris School of Business, PSBSaint-Denis CedexFrance

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