Skip to contents

Dynamic Spillover

Source: R/spillover.R, R/print-spillover.R
dynamic_spillover.Rd

This function gives connectedness table with h-step ahead normalized spillover index (a.k.a. variance shares).

Usage

dynamic_spillover(object, n_ahead = 10L, ...)

# S3 method for class 'bvhardynsp'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

# S3 method for class 'bvhardynsp'
knit_print(x, ...)

# S3 method for class 'olsmod'
dynamic_spillover(object, n_ahead = 10L, window, num_thread = 1, ...)

# S3 method for class 'normaliw'
dynamic_spillover(
  object,
  n_ahead = 10L,
  window,
  num_iter = 1000L,
  num_burn = floor(num_iter/2),
  thinning = 1,
  num_thread = 1,
  ...
)

# S3 method for class 'ldltmod'
dynamic_spillover(
  object,
  n_ahead = 10L,
  window,
  sparse = FALSE,
  num_thread = 1,
  ...
)

# S3 method for class 'svmod'
dynamic_spillover(object, n_ahead = 10L, sparse = FALSE, num_thread = 1, ...)

Arguments

object

Model object

n_ahead

step to forecast. By default, 10.

...

not used

x

bvhardynsp object

digits

digit option to print

window

Window size

num_thread

[Experimental] Number of threads

num_iter

Number to sample MNIW distribution

num_burn

Number of burn-in

thinning

Thinning every thinning-th iteration

sparse

[Experimental] Apply restriction. By default, FALSE.

References

Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of forecasting, 28(1), 57-66.