• DocumentCode
    11953
  • Title

    Financial Crisis Forecasting via Coupled Market State Analysis

  • Author

    Wei Cao ; Longbing Cao

  • Author_Institution
    Univ. of Technol., Sydney, NSW, Australia
  • Volume
    30
  • Issue
    2
  • fYear
    2015
  • fDate
    Mar.-Apr. 2015
  • Firstpage
    18
  • Lastpage
    25
  • Abstract
    Financial crisis forecasting has been a long-standing challenge that often involves couplings between indicators of multiple markets. Such couplings include implicit relations that might not be effectively detected from raw market observations. However, most methods for crisis forecasting rely directly on market observations and might not detect the hidden interactions between markets. To this end, the authors explore coupled market state analysis (CMSA), assuming that the observations of markets are governed by a collection of intra- and intercoupled hidden market states. Accordingly, they built a forecaster based on these coupled market states instead of observations.
  • Keywords
    economic cycles; financial data processing; CMSA; coupled market state analysis; financial crisis forecasting; intercoupled hidden market states; raw market observations; Business; Forecasting; Hidden Markov models; Logistics; Marketing and sales; Mathematical model; Predictive models; coupled hidden Markov model; coupled market state analysis; forecasting; intelligent systems;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2015.4
  • Filename
    7006348