Boot.test {vrtest}

Bootstrap Variance Ratio Tests

Description

This function returns bootstrap p-values of the Lo-MacKilay (1988) and Chow-Denning (1993) tests.

Users can choose between iid bootstrap and wild bootstrap

Usage

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

Arguments

y

a vector of time series, typically financial return

kvec

a vector of holding periods

nboot

the number of bootstrap iterations

wild

"No" for iid bootstrap, "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

Holding.Period

holding periods used

LM.pval

Bootstrap p-values for the Lo-MacKinlay tests

CD.pval

Bootstrap p-value for the Chow-Denning test

CI

Confidence Intervals for Lo-Mackinlay tests from Bootstrap distribution

Author(s)

Jae H. Kim

References

Kim, J.H., 2006, Wild Bootstrapping Variance Ratio Tests. Economics Letters, 92, 38-43.

Examples

data(exrates)
y <- exrates$ca                   
nob <- length(y)
r <- log(y[2:nob])-log(y[1:(nob-1)])    
kvec <- c(2,5,10)
Boot.test(r,kvec,nboot=500,wild="Normal")