Hidden Markov Models

Applications to Financial Economics

  • Ramaprasad Bhar
  • Shigeyuki Hamori

Part of the Advanced Studies in Theoretical and Applied Econometrics book series (ASTA, volume 40)

About this book

Introduction

Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. Although the hidden Markov processes have been widely employed for some time in many engineering applications e.g. speech recognition, its effectiveness has now been recognized in areas of social science research as well. The main aim of Hidden Markov Models: Applications to Financial Economics is to make such techniques available to more researchers in financial economics. As such we only cover the necessary theoretical aspects in each chapter while focusing on real life applications using contemporary data mainly from OECD group of countries. The underlying assumption here is that the researchers in financial economics would be familiar with such application although empirical techniques would be more traditional econometrics. Keeping the application level in a more familiar level, we focus on the methodology based on hidden Markov processes. This will, we believe, help the reader to develop more in-depth understanding of the modeling issues thereby benefiting their future research.

Keywords

Inflation Markov Chain Markov Chains econometrics linear optimization modeling paraplupub production

Authors and affiliations

  • Ramaprasad Bhar
    • 1
  • Shigeyuki Hamori
    • 2
  1. 1.School of Banking and FinanceThe University of New South WalesSydneyAustralia
  2. 2.Graduate School of EconomicsKobe UniversityJapan

Bibliographic information

  • DOI https://doi.org/10.1007/b109046
  • Copyright Information Springer Science + Business Media, Inc. 2004
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4020-7899-6
  • Online ISBN 978-1-4020-7940-5
  • Series Print ISSN 1570-5811
  • About this book