Bayesian dynamic financial networks with time-varying predictors

2014/03/10 by Daniele Durante, David B. Dunson · 31 citations
Economics, Econometrics and Finance · Mathematics · #Artificial intelligence #Banking stability, regulation, efficiency #Bayesian inference #Bayesian probability #Complex Systems and Time Series Analysis #Computer science #Dynamic Bayesian network #Econometrics #Economics #Finance #Financial Risk and Volatility Modeling #Financial crisis #Financial econometrics #Financial market #Indirect finance #Inference #Mathematics #Statistics #stat.AP #stat.ME

paper · pdf · doi:10.1016/j.spl.2014.06.015

published in Statistics & Probability Letters 93, 19-26 (Elsevier BV)

arxiv created 2014/03/10 · openalex publication_date 2014/06/20 · arxiv updated 2014/07/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

We propose a Bayesian nonparametric model including time-varying predictors in dynamic network inference. The model is applied to infer the dependence structure among financial markets during the global financial crisis, estimating effects of verbal and material cooperation efforts. We interestingly learn contagion effects, with increasing influence of verbal relations during the financial crisis and opposite results during the United States housing bubble.

Citations

• Common risk factors in the returns on stocks and bonds
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
• Collective behavior in financial market