inference.classic: Classic T-inference for event study estimator

In eventstudies: Event Study Analysis

Description

This function uses standard student's t-statistic to obtain the estimate for response of the event and the corresponding confidence intervals.

Usage

inference.classic(es.w,
                  to.plot = TRUE,
                  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.
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 inference drawn using student's inference.

Author(s)

Sargam Jain

See Also

boot phys2eventtime inference.wilcox inference.bootstrap

Examples

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.classic(es.w = eventtime,
                  to.plot = FALSE)

Example output

Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: xts
           2.5%        Mean    97.5%
 [1,]       NaN  0.00000000      NaN
 [2,] -1.769804 -0.04963427 1.670535
 [3,] -1.824798  0.11112653 2.047051
 [4,] -2.832604 -0.02981150 2.772981
 [5,] -1.176208  0.16682379 1.509856
 [6,] -3.910083 -1.12396803 1.662147
 [7,] -7.207655 -1.34188821 4.523879
 [8,] -6.223253 -0.96626653 4.290720
 [9,] -3.914495  0.08482258 4.084140
[10,] -4.152251  0.52233286 5.196917
[11,] -4.328110  0.02624783 4.380606

eventstudies documentation built on July 1, 2020, 10:26 p.m.