Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we devel...

Regime Switching Garch Models

We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past information. We provide sufficient conditions for geometric ergodicity and existence of moments. Because of path dependence, maximum likelihood estimation is no...

Regime - Switching Models

Regime-Switching Factor Models for High-Dimensional Time Series

We consider a factor model for high-dimensional time series with regime-switching dynamics. The switching is assumed to be driven by an unobserved Markov chain; the mean, factor loading matrix and covariance matrix of the noise process are different among the regimes. The model is an extension of the traditional factor models for time series and provides flexibility in dealing with real applica...

Regime Switching Models for Markets

Search for structure in the financial markets has recently become an active field of research by scientists from different areas of expertise. The Efficient-Market Hypothesis states that the markets reflect all publically available information within their price. This also means that no profit higher than the average market returns allow can be gained using only the price information. However, ...