Hidden Markov Models in Finance

  • Rogemar S. Mamon
  • Robert J. Elliott

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 104)

Table of contents

About this book

Introduction

A number of methodologies have been employed to provide decision making solutions to a whole assortment of financial problems in today's globalized markets. Hidden Markov Models in Finance by Mamon and Elliott will be the first systematic application of these methods to some special kinds of financial problems; namely, pricing options and variance swaps, valuation of life insurance policies, interest rate theory, credit risk modeling, risk management, analysis of future demand and inventory level, testing foreign exchange rate hypothesis, and early warning systems for currency crises. This book provides researchers and practitioners with analyses that allow them to sort through the random "noise" of financial markets (i.e., turbulence, volatility, emotion, chaotic events, etc.) and analyze the fundamental components of economic markets. Hence, Hidden Markov Models in Finance provides decision makers with a clear, accurate picture of core financial components by filtering out the random noise in financial markets.

 

Keywords

Finance Markov Markov chain Markov model Markov models Variance credit risk modeling early warning systems interest rates inventory system life insurance valuation market risk model modeling regime-switching

Editors and affiliations

  • Rogemar S. Mamon
    • 1
  • Robert J. Elliott
    • 2
  1. 1.University of Western OntarioLondonCanada
  2. 2.University of CalgaryCalgaryCanada

Bibliographic information

  • DOI https://doi.org/10.1007/0-387-71163-5
  • Copyright Information Springer Science+Business Media, LLC 2007
  • Publisher Name Springer, Boston, MA
  • eBook Packages Business and Economics
  • Print ISBN 978-0-387-71081-5
  • Online ISBN 978-0-387-71163-8
  • Series Print ISSN 0884-8289
  • About this book