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
Link To Document