# AutoBoot.test {vrtest}

### 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

### Values

- 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

### 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, in press.

### Examples

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

Documentation reproduced from package vrtest, version 0.97. License: GPL-2