Bayesian dynamic financial networks with time-varying predictors |
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| Affiliation: | 1. Regional Institute of Oncology, Iasi, Romania;2. Faculty of Physics, Alexandru Ioan Cuza University, Iasi, Romania;3. Department of Biomedical Sciences, Faculty of Medical Bioengineering, “Grigore T. Popa” University of Medicine and Pharmacy, Iasi, Romania |
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| 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. |
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| Keywords: | Co-movement Edge covariates Financial network Gaussian process Latent space |
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