AutoBoot.test: Wild Bootstrapping of Automatic Variance Ratio Test

In vrtest: Variance Ratio Tests and Other Tests for Martingale Difference Hypothesis

Wild Bootstrapping of Automatic Variance Ratio Test

Description

This function returns wild bootstrap test results for the Automatic Variance Ratio Test of Choi (1999)

Usage

AutoBoot.test(y, nboot, wild,prob=c(0.025,0.975))

Arguments

y	a vector of time series, typically financial return
nboot	the number of bootstrap iterations
wild	"Normal" for the wild bootstrap using the standard normal distribution, "Mammen" for the wild bootstrap using Mammen's two point distribution, "Rademacher" for the wild bootstrap using Rademacher's two point distribution
prob	probability limits for confidence intervals

Value

test.stat	Automatic variance ratio test statistic
VRsum	1+ weighted sum of autocorrelation up to the optimal order
pval	Wild Bootstrap p-value for the test
CI	Confidence Intervals for the test statistic from Bootstrap distribution
CI.VRsum	Confidence Intervals for the VRsum from Bootstrap distribution

Author(s)

Jae H. Kim

References

Kim, J. H., 2009, Automatic Variance Ratio Test under Conditional Heteroskedascity, Finance Research Letters, 6(3), 179-185.

Charles, A. Darne, O. Kim, J.H. 2011, Small Sample Proeprties of Alternative Tests for Martingale Difference Hypothesis, Economics Letters, 110(2), 151-154.

Examples

                                
r <- rnorm(100)          
AutoBoot.test(r,nboot=500,wild="Normal")

vrtest documentation built on Aug. 31, 2023, 9:08 a.m.