View source: R/car_parametric_tests.R
| car_parametric_tests | R Documentation | 
Performs given tests to examine whether cumulative abnormal return (CAR) significantly differs from zero.
car_parametric_tests(
  list_of_returns,
  car_start,
  car_end,
  percentage = 90,
  all = TRUE,
  tests
)
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.  | 
all | 
 a logical value indicating whether all tests should be performed.
The default value is   | 
tests | 
 a list of tests' functions among   | 
car_parametric_tests performs specified tests among
car_brown_warner_1985 and lamb and returns a list of these
tests' results. If all = TRUE (by default), the function ignores the
value of tests.
A data frame of the following columns:
name: a name of the test
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
Brown S.J., Warner J.B. Using Daily Stock Returns, The Case of Event Studies. Journal of Financial Economics, 14:3-31, 1985.
Lamb R.P. An Exposure-Based Analysis of Property-Liability Insurer Stock Values around Hurricane Andrew. Journal of Risk and Insurance, 62(1):111-123, 1995.
car_brown_warner_1985 and car_lamb.
## 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")
car_param <- 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_parametric_tests(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_param <- car_parametric_tests(
    list_of_returns = securities_returns,
    car_start = as.Date("2020-03-16"),
    car_end = as.Date("2020-03-20")
)
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