TVPVAR {ConnectednessApproach}

Time-varying parameter vector autoregression

Description

Estimate TVP-VAR model

Usage

TVPVAR(x, configuration = list(l = c(0.99, 0.99), nlag = 1, prior = NULL))

Arguments

x

zoo data matrix

configuration

model configuration

nlag

Lag length

prior

List of prior VAR coefficients and variance-covariance matrix

l

forgetting factors (kappa1, kappa2)

Value

Estimate TVP-VAR model

Author(s)

David Gabauer

References

Koop, G., & Korobilis, D. (2014). A new index of financial conditions. European Economic Review, 71, 101-116.

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, 13(4), 84.

Examples

data("dy2012")
prior = BayesPrior(dy2012, nlag=1)
fit = TVPVAR(dy2012, configuration=list(nlag=1, prior=prior, l=c(0.99,0.99)))