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Bayesian dynamic financial networks with time-varying predictors

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  • Durante, Daniele
  • Dunson, David B.

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.

Suggested Citation

  • Durante, Daniele & Dunson, David B., 2014. "Bayesian dynamic financial networks with time-varying predictors," Statistics & Probability Letters, Elsevier, vol. 93(C), pages 19-26.
    • Handle: RePEc:eee:stapro:v:93:y:2014:i:c:p:19-26
    DOI: 10.1016/j.spl.2014.06.015
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    References listed on IDEAS

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    Cited by:

    1. Piero Mazzarisi & Paolo Barucca & Fabrizio Lillo & Daniele Tantari, 2017. "A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market," Papers 1801.00185, arXiv.org.
    2. Fengrong Wei, 2018. "A Short Discussion of Network Analysis," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(2), pages 12-13, June.

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