AutoBoot.test {vrtest}

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")