R2Connectedness: R2 connectedness approach

In ConnectednessApproach: Connectedness Approach

R2 connectedness approach

Description

This function computes the R2 connectedness measures

Usage

R2Connectedness(
  x,
  window.size = NULL,
  nlag = 0,
  method = "pearson",
  relative = FALSE,
  corrected = FALSE
)

Arguments

x	zoo data matrix
window.size	Rolling-window size or Bayes Prior sample size
nlag	Lag length
method	"pearson", "spearman", or "kendall". "pearson" is default.
relative	Boolean whether relative or absolute R2 should be used
corrected	Boolean value whether corrected or standard TCI should be computed

Value

Get R2 connectedness measures

Author(s)

David Gabauer

References

Naeem, M. A., Chatziantoniou, I., Gabauer, D., & Karim, S. (2023). Measuring the G20 Stock Market Return Transmission Mechanism: Evidence From the R2 Connectedness Approach. International Review of Financial Analysis.

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, 57, 104168.

Examples

data("dy2012")
dca = R2Connectedness(dy2012, window.size=NULL, nlag=0, method="pearson")
dca$TABLE

ConnectednessApproach documentation built on June 22, 2024, 10:22 a.m.