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.

Bayesian dynamic financial networks with time-varying predictors

DURANTE, DANIELE;
2014

Abstract

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.
2014
Durante, Daniele; Dunson, David B.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11565/3998959
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