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.
File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
SPL_Durante2014.pdf
non disponibili
Descrizione: Publisher's layout version is available at the URL provided.
Tipologia:
Documento in Post-print (Post-print document)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
530.41 kB
Formato
Adobe PDF
|
530.41 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
