Brown and Warner (1985) CAR test.

Source: R/car_parametric_tests.R

A parametric test proposed by Brown and Warner 1995 that examines whether or not cumulative abnormal return (CAR) significantly differs from zero.

car_brown_warner_1985(list_of_returns, car_start, car_end, percentage = 90)

Arguments

list_of_returns

a list of objects of S3 class returns, each element of which is treated as a security.
car_start

an object of Date class giving the first date of the CAR period.
car_end

an object of Date class giving the last date of the CAR period.
percentage

a lowest allowed percentage of non-missing observation for each day to be incorporated into CAR. The default value is 90 percent.

  • name: a name of the test, i.e. "car_brown_warner_1985"

  • car_start: the first date of the CAR period

  • car_end: the last date of the CAR period

  • average_percentage: an average share of non-missing observations over the CAR period

  • car_mean: an average abnormal return over the CAR period

  • statistic: a test's statistic

  • number_of_days: the number of days in the CAR period

  • significance: a significance of the statistic

Details

This function performs a test proposed by Brown and Warner 1985 to investigate whether CAR significantly differs from zero. This tests uses the variance, specified by Brown and Warner 1985. The advantage of this test is allowance for correlated cross-sectional returns. However, the test does not use autocorrelation adjustment. The test statistic is close enough to statistic, produced by car_lamb. The critical values are standard normal. The significance levels of \(\alpha\) are 0.1, 0.05, and 0.01 (marked respectively by *, **, and ***).

References

Brown S.J., Warner J.B. Using Daily Stock Returns, The Case of Event Studies. Journal of Financial Economics, 14:3-31, 1985.

See also

car_lamb and car_parametric_tests.

Examples

if (FALSE) {
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_brown_warner_1985(car_start = as.Date("2020-03-16"),
                          car_end = as.Date("2020-03-20"))
}
## The result of the code above is equivalent to:
data(securities_returns)
car_brown_warner_1985(
    list_of_returns = securities_returns,
    car_start = as.Date("2020-03-16"),
    car_end = as.Date("2020-03-20")
)

#>                    name  car_start    car_end average_percentage   car_mean
#> 1 car_brown_warner_1985 2020-03-16 2020-03-20                100 0.02213319
#>   statistic number_of_days significance
#> 1  3.948093              5          ***