This function allows you to specify the window length k when estimating the Z-score. It is similar to Z2 in the sense that CAR is left observable per time t, but ROA sigma and mean are estimated on a rolling basis, where k is the window length specified for computing the rolling estimates. The difference between Z6_2 and Z6_3 is that Z6_2 corrects for the unbiasedness of the sample standard deviation by using a simple approximation of Cochran's theorem thorugh exploiting the correction factor for the estimator of the coefficient of variation according to Salkind(2010). Z6_3 on the other hand, uses the more appropriate correction factor by applying the mean of a chi distribution.
1 |
data |
The dataset of interest. Note that ROA should be in column number 3 and CAR in column number 4. |
k |
The window length k for calculating the rolling mean and sigma with rollapply. |
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