When calculating the car_mean in car_parametric_tests, only the mean of the ARs are calculated - there is no cumulative summation.
e.g., for the calculation of car_mean in the car_lamb process, in car_parametric.R :
car_mean <- mean(daily_lamb_statistics_tidy[, 4], na.rm = TRUE)
This takes the ARs from daily_lamb_statistics_tidy and calculates the mean.
There is no accumulation of the ARs prior to calculating the mean, and therefore it is not a cumulative average abnormal return.
Thus all that is provided is the longitudinal mean of ARs. These ARs are already the cross-sectional averages (which is correct - might be clearer to change the name to AARs as is typical in literature i.e. Average Abnormal Returns).
Thus it would be more useful to provide the CAAR (Cumulative Average Abnormal Return) by calculating it as:
caar <- sum(daily_lamb_statistics_tidy[, 4], na.rm = TRUE)
@keegangclarke, thanks for the issue. I will look into it during the weekend. Can you please let me know if this is related to this issue? There was also confusion with names.
When calculating the
car_mean
incar_parametric_tests
, only the mean of the ARs are calculated - there is no cumulative summation.e.g., for the calculation of
car_mean
in thecar_lamb
process, incar_parametric.R
:car_mean <- mean(daily_lamb_statistics_tidy[, 4], na.rm = TRUE)
This takes the ARs from
daily_lamb_statistics_tidy
and calculates the mean. There is no accumulation of the ARs prior to calculating the mean, and therefore it is not a cumulative average abnormal return.Thus all that is provided is the longitudinal mean of ARs. These ARs are already the cross-sectional averages (which is correct - might be clearer to change the name to AARs as is typical in literature i.e. Average Abnormal Returns). Thus it would be more useful to provide the CAAR (Cumulative Average Abnormal Return) by calculating it as:
caar <- sum(daily_lamb_statistics_tidy[, 4], na.rm = TRUE)