View source: R/car_nonparametric_tests.R
car_rank_test | R Documentation |
A nonparametric test proposed by Cowan 1992 as an extension of the rank test proposed by Corrado 1989.
car_rank_test(list_of_returns, car_start, car_end, percentage = 90)
list_of_returns |
a list of objects of S3 class |
car_start |
an object of |
car_end |
an object of |
percentage |
a lowest allowed percentage of non-missing observation for each day to be incorporated into CAR. The default value is 90 percent.
|
This function performs a test proposed by Cowan 1992 to investigate the
significance of the CAR for a given period. In order to get ranks of
corresponding abnormal returns, the procedure uses regular R function
rank
with parameter ties.method = "average"
and
na.last = "keep"
. For this test the estimation period and the event
period must not overlap, otherwise an error will be thrown. The test
statistic is assumed to have a normal distribution (as an approximation). The
test is well-specified for the case, when cross-sectional abnormal returns
are not symmetric. The test is stable to variance increase during given
period. This test ignores the dependence of abnormal returns' ranks of
different days (i.e., a serial dependence). The critical values are standard
normal. The significance levels of α are 0.1, 0.05, and 0.01
(marked respectively by *, **, and ***).
Corrado C.J. A Nonparametric Test for Abnormal Security-Price Performance in Event Studies. Journal of Financial Economics 23:385-395, 1989.
Cowan A.R. Nonparametric Event Study Tests. Review of Quantitative Finance and Accounting, 2:343-358, 1992.
car_nonparametric_tests
.
## Not run: library("magrittr") rates_indx <- get_prices_from_tickers("^GSPC", start = as.Date("2019-04-01"), end = as.Date("2020-04-01"), quote = "Close", retclass = "zoo") %>% get_rates_from_prices(quote = "Close", multi_day = TRUE, compounding = "continuous") tickers <- c("AMZN", "ZM", "UBER", "NFLX", "SHOP", "FB", "UPWK") get_prices_from_tickers(tickers, start = as.Date("2019-04-01"), end = as.Date("2020-04-01"), quote = "Close", retclass = "zoo") %>% get_rates_from_prices(quote = "Close", multi_day = TRUE, compounding = "continuous") %>% apply_market_model(regressor = rates_indx, same_regressor_for_all = TRUE, market_model = "sim", estimation_method = "ols", estimation_start = as.Date("2019-04-01"), estimation_end = as.Date("2020-03-13")) %>% car_rank_test(car_start = as.Date("2020-03-16"), car_end = as.Date("2020-03-20")) ## End(Not run) ## The result of the code above is equivalent to: data(securities_returns) car_rank_test( list_of_returns = securities_returns, car_start = as.Date("2020-03-16"), car_end = as.Date("2020-03-20") )
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