| Panel.VR {vrtest} | R Documentation |
Panel Variance Ratio Tests
Description
Panel variance tatio tests based on Maximum Absloute Value, Sum of Squares, and Mean of each cross-sectional units
Usage
Panel.VR(dat, nboot = 500)
Arguments
dat |
a T by K matrix of asset returns, K is the munber of cross sectional units and T is length of time series |
nboot |
the number of wild bootstrap iterations, the default is set to 500 |
Details
The component statistics are based on the automatic variance ratio test The set of returns are wild bootstrapped to conserve cross-sectional dependency
Value
MaxAbs.stat |
the statistic based on the maximum absolute value of individual statistics |
SumSquare.stat |
the statistic based on the sum of squared value of individual statistics |
Mean.stat |
the statistic based on the mean value of individual statistics |
MaxAbs.pval |
the wild bootstrap pvalue based on the maximum absolute value of individual statistics |
SumSquare.pval |
the wild bootstrap pvalue based on the sum of squared value of individual statistics |
Mean.pval |
the wild bootstrap pvalue based on the mean value of individual statistics |
Author(s)
Jae H. Kim
References
Kim, J. H., & Shamsuddin, A. (2015). A closer look at return predictability of the US stock market: evidence from new panel variance ratio tests. Quantitative Finance, 15(9), 1501-1514.
Examples
ret=matrix(rnorm(200),nrow=100)
Panel.VR(ret)