Panel.VR: Panel Variance Ratio Tests

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

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)

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