Arbeitspapier

Bayesian SAR model with stochastic volatility and multiple time-varying weights

A novel spatial autoregressive model for panel data is introduced, which incorporates multilayer networks and accounts for time-varying relationships. Moreover, the proposed approach allows the structural variance to evolve smoothly over time and enables the analysis of shock propagation in terms of time-varying spillover effects. The framework is applied to analyse the dynamics of international relationships among the G7 economies and their impact on stock market returns and volatilities. The findings underscore the substantial impact of cooperative interactions and highlight discernible disparities in network exposure across G7 nations, along with nuanced patterns in direct and indirect spillover effects.

Language
Englisch

Bibliographic citation
Series: SAFE Working Paper ; No. 407

Classification
Wirtschaft
Bayesian Analysis: General
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Model Construction and Estimation
Financial Econometrics
Subject
Bayesian inference
International relationships
Multilayer networks
Spatial autoregressive model
Time-varying networks
Stochastic volatility

Event
Geistige Schöpfung
(who)
Costola, Michele
Iacopini, Matteo
Wichers, Casper
Event
Veröffentlichung
(who)
Leibniz Institute for Financial Research SAFE
(where)
Frankfurt a. M.
(when)
2023

DOI
doi:10.2139/ssrn.4620913
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Costola, Michele
  • Iacopini, Matteo
  • Wichers, Casper
  • Leibniz Institute for Financial Research SAFE

Time of origin

  • 2023

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