View source: R/ConnectednessApproach.R
ConnectednessApproach | R Documentation |
This function provides a modular framework combining various models and connectedness frameworks.
ConnectednessApproach(
x,
nlag = 1,
nfore = 10,
window.size = NULL,
corrected = FALSE,
model = c("VAR", "QVAR", "LAD", "LASSO", "Ridge", "Elastic", "TVP-VAR", "DCC-GARCH"),
connectedness = c("Time", "Frequency", "Joint", "Extended Joint", "R2"),
VAR_config = list(QVAR = list(tau = 0.5, method = "fn"), ElasticNet = list(nfolds = 10,
alpha = NULL, loss = "mae", n_alpha = 10), TVPVAR = list(kappa1 = 0.99, kappa2 =
0.99, prior = "BayesPrior", gamma = 0.01)),
DCC_config = list(standardize = FALSE),
Connectedness_config = list(TimeConnectedness = list(generalized = TRUE),
FrequencyConnectedness = list(partition = c(pi, pi/2, 0), generalized = TRUE,
scenario = "ABS"), R2Connectedness = list(method = "pearson", decomposition = TRUE,
relative = FALSE))
)
x |
zoo data matrix |
nlag |
Lag length |
nfore |
H-step ahead forecast horizon |
window.size |
Rolling-window size or Bayes Prior sample size |
corrected |
Boolean value whether corrected or standard TCI should be computed |
model |
Estimation model |
connectedness |
Type of connectedness approach |
VAR_config |
Config for VAR model |
DCC_config |
Config for DCC-GARCH model |
Connectedness_config |
Config for connectedness approach |
Get connectedness measures
David Gabauer
Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., & Oliyide, J. (2022). Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies. Resources Policy.
Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management.
Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2020). Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness. Energy Economics.
Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2021). The impact of Euro through time: Exchange rate dynamics under different regimes. International Journal of Finance & Economics.
Balcilar, M., Gabauer, D., & Umar, Z. (2021). Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach. Resources Policy.
Balli, F., Balli, H. O., Dang, T. H. N., & Gabauer, D. (2023). Contemporaneous and lagged R2 decomposed connectedness approach: New evidence from the energy futures market. Finance Research Letters.
Barunik, J., & Krehlik, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics.
Broadstock, D. C., Chatziantoniou, I., & Gabauer, D. (2022). Minimum connectedness portfolios and the market for green bonds: Advocating socially responsible investment (SRI) activity. In Applications in energy finance: The energy sector, economic activity, financial markets and the environment. Cham: Springer International Publishing.
Chatziantoniou, I., & Gabauer, D. (2021). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. The Quarterly Review of Economics and Finance.
Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach. Economics Letters.
Chatziantoniou, I., Gabauer, D., & Gupta, R. (2023). Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach. Resources Policy.
Chatziantoniou, I., Aikins Abakah, E. J., Gabauer, D., & Tiwari, A. K. (2022). Quantile time-frequency price connectedness between green bond, green equity, sustainable investments and clean energy markets. Journal of Cleaner Production.
Chatziantoniou, I., Elsayed, A. H., Gabauer, D., & Gozgor, G. (2023). Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies. Energy Economics.
Cocca, T., Gabauer, D., & Pomberger, S. (2024). Clean energy market connectedness and investment strategies: New evidence from DCC-GARCH R2 decomposed connectedness measures. Energy Economics.
Cunado, J., Chatziantoniou, I., Gabauer, D., de Gracia, F. P., & Hardik, M. (2023). Dynamic spillovers across precious metals and oil realized volatilities: Evidence from quantile extended joint connectedness measures. Journal of Commodity Markets.
Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal.
Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting.
Gabauer, D. (2020). Volatility impulse response analysis for DCC-GARCH models: The role of volatility transmission mechanisms. Journal of Forecasting.
Gabauer, D. (2021). Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system. Journal of Multinational Financial Management.
Gabauer, D., Chatziantoniou, I., & Stenfors, A. (2023). Model-free connectedness measures. Finance Research Letters.
Gabauer, D., Gupta, R., Marfatia, H. A., & Miller, S. M. (2024). Estimating US housing price network connectedness: Evidence from dynamic Elastic Net, Lasso, and ridge vector autoregressive models. International Review of Economics & Finance.
Gabauer, D., & Stenfors, A. (2024). Quantile-on-quantile connectedness measures: Evidence from the US treasury yield curve. Finance Research Letters, 60, 104852.
Lastrapes, W. D., & Wiesen, T. F. (2021). The joint spillover index. Economic Modelling, 94, 681-691.
Naeem, M. A., Chatziantoniou, I., Gabauer, D., & Karim, S. (2024). Measuring the G20 stock market return transmission mechanism: Evidence from the R2 connectedness approach. International Review of Financial Analysis.
Stenfors, A., Chatziantoniou, I., & Gabauer, D. (2022). Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves. Journal of International Financial Markets, Institutions and Money.
Zhang, Y., Gabauer, D., Gupta, R., & Ji, Q. (2024). How connected is the oil-bank network? Firm-level and high-frequency evidence. Energy Economics.
data("acg2020")
dca = ConnectednessApproach(acg2020,
nlag=1,
nfore=12,
model="VAR",
connectedness="Time",
VAR_config=list(TVPVAR=list(kappa1=0.99, kappa2=0.96,
prior="MinnesotaPrior", gamma=0.1)))
dca$TABLE
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