Bayesian dynamic financial networks with time-varying predictors

We propose a targeted and robust modeling of dependence in multivariate time series via dynamic networks, with time-varying predictors included to improve interpretation and prediction. The model is applied to financial markets, estimating effects of verbal and material cooperations.

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Year of publication:	2014
Authors:	Durante, Daniele ; Dunson, David B.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 93.2014, C, p. 19-26
Publisher:	Elsevier
Subject:	Co-movement \| Edge covariates \| Financial network \| Gaussian process \| Latent space

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010906224