eventstudies (version 1.2.2)

inference.bootstrap: Bootstrap inference for event study estimator

Description

This function obtains a boostrapped confidence interval for estimates of magnitude over the event horizon.

Usage

inference.bootstrap(es.w,
                   to.plot = TRUE,
                   boot.run = 1000,
                   xlab = "Event time", 
		   ylab = "Cumulative returns of response series", 
		   main = "Event study plot")

Arguments

es.w

a zoo object indexed by event time: the “z.e” component of the list returned by the phys2eventtime function. The object should consist of more than one series.

boot.run

A ‘numeric’, controlling the number of simulations required for the bootstrap.

to.plot

a ‘logical’ indicating whether to generate an event study plot of the inference estimated. Defaults to ‘TRUE’.

xlab

the x-axis label of the generated plot. Used if “to.plot” is ‘TRUE’.

ylab

the y-axis label of the generated plot. Used if “to.plot” is ‘TRUE’.

main

main title of the plot. Used if “to.plot” is ‘TRUE’.

Value

A ‘matrix’ with 3 columns, the lower confidence interval (CI), the mean, and the upper CI which are the result of bootstrap inference.

See Also

boot phys2eventtime inference.wilcox inference.classic

Examples

# NOT RUN {
data(StockPriceReturns)
data(SplitDates)

es.results <- phys2eventtime(z = StockPriceReturns,
                             events = SplitDates,
                             width = 5)
es.w <- window(es.results$z.e,
               start = -5,
               end = +5)

eventtime <- remap.cumsum(es.w, is.pc = FALSE, base = 0)
inference.bootstrap(es.w = eventtime,
                    to.plot = FALSE)
# }