Title :
Financial Crisis Forecasting via Coupled Market State Analysis
Author :
Wei Cao ; Longbing Cao
Author_Institution :
Univ. of Technol., Sydney, NSW, Australia
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;
Journal_Title :
Intelligent Systems, IEEE