car_parametric_tests: Returns the result of given event study parametric CAR tests.
In estudy2: An Implementation of Parametric and Nonparametric Event Study

Description Usage Arguments Details Value References See Also Examples

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 `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.
`all`	a logical value indicating whether all tests should be performed. The default value is `TRUE`.
`tests`	a list of tests' functions among `car_brown_warner_1985` and `car_lamb`.

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")
)