Pattern recognition using hidden Markov models in financial time series

  • Sara Rebagliati Università degli Studi di Genova, Dipartimento di Matematica, Via Dodecaneso 35, 16146 Genova
  • Emanuela Sasso Università degli Studi di Genova, Dipartimento di Matematica, Via Dodecaneso 35, 16146 Genova
Keywords: pattern recognition, hidden Markov models, financial time series, automated trading system

Abstract

Our aim consists in developing a software which can recognize M trading patterns in real time using Hidden Markov Models (HMMs). A trading pattern is a predefined figure indicating a specific behavior of prices. We trained M + 1 HMMs using Baum-Welch Algorithm combined with Genetic Algorithm. In particular, with HMMs we describe M trading patterns while the other one, called threshold model, can recognize all the not predefined patterns. The classification algorithm correctly recognizes 93% of the provided patterns. Thanks to the analysis of the false positive examples, we finally designed some more filters to reduce them.
Published
2017-07-03
Section
Articles