Connectedness Approach
Quantile vector autoregression
R2 decomposed connectedness from correlations
R2 connectedness approach
Generalized volatility forecast error variance decomposition and volat...
Baruník and Křehlík (2018) frequency connectedness approach
Aggregated Connectedness Measures
Bayes Prior
Network plot
Dynamic net pairwise connectedness plot
Dynamic net pairwise transmission plot
Dynamic pairwise connectedness plot
Dynamic total connectedness plot
Dynamic to total directional connectedness plot
Bivariate DCC-GARCH
Kroner and Ng (1998) optimal bivariate portfolio weights
ConditionalConnectedness
Partial Conditional Correlations
Connectedness Approach
Connectedness table
DCC-GARCH selection specification
Lastrapes and Wiesen (2021) joint connectedness approach
Elastic Net vector autoregression
Equally weighted portfolio
Exclusive Connectedness Measures
Balcilar et al. (2021) extended joint connectedness approach
External Connectedness Measures
Forecast error variance decomposition
Univariate GARCH selection criterion
Univariate GARCH test statistics
Kroner and Sultan (1993) hedge ratios
Inclusive Connectedness Measures
Internal Connectedness Measures
Impulse response functions
Least absolute deviation vector autoregression
Minimum connectedness portfolio
Minnesota Prior
Multivariate Hedging Portfolio
Partial Contemporaneous Correlations
Dynamic from total directional connectedness plot
Dynamic influence connectedness plot
Dynamic net total directional connectedness plot
Minimum connectedness portfolio
Summary Statistics
Diebold and Yilmaz (2009, 2012) connectedness approach
Time-varying parameter vector autoregression
Uninformative Prior
Vector autoregression
Variance Test
WeightedBoxTest
Wold representation theorem
The estimation of static and dynamic connectedness measures is created in a modular and user-friendly way. Besides, the time domain connectedness approaches, this package further allows to estimate the frequency connectedness approach, the joint spillover index and the extended joint connectedness approach. In addition, all connectedness frameworks can be based upon orthogonalized and generalized VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR and TVP-VAR models. Furthermore, the package includes the conditional, decomposed and partial connectedness measures as well as the pairwise connectedness index, influence index and corrected total connectedness index. Finally, a battery of datasets are available allowing to replicate a variety of connectedness papers.