Title: A new online method for event detection and tracking: empirical evidence from the French stock market
Authors: Mohamed Saidane, Christian Lavergne
Addresses: Department of Quantitative Methods, University of 7 November at Carthage, ISCC de Bizerte, Zarzouna 7021, Tunisia. ' Department of Mathematics, University of Montpellier II, 13M UMR-CNRS 5149, CC, 051, 34095 Montpellier, France
Abstract: In this article we propose a new approach in event studies based on a hidden Markov chain combined with a classical event study model. The number of states informs us about the number of significant events affecting the related market, and the identification of the hidden states determines exactly the delimiters of the event period. Studying each state parameters allows us to examine the events| effect on the related market and to compare results to traditional event analysis. Extensive Monte Carlo simulations and preliminary examination of real data in the French stock market show promising results.
Keywords: constant mean return model; CMRM; EM algorithm; event study; event detection; event tracking; France; French stock market; HMM; hidden Markov model; market models; model selection.
American Journal of Finance and Accounting, 2008 Vol.1 No.1, pp.20 - 51
Published online: 13 Aug 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article