inference.wilcox: Wilcox inference for event study estimator

In eventstudies: Event Study Analysis

Description

This function does wilcox inference to generate distribution of average of all the cumulative returns time-series.

Usage

inference.wilcox(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 wilcox inference.

Author(s)

Vikram Bahure, Vimal Balasubramaniam

See Also

phys2eventtime inference.bootstrap inference.classic

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.wilcox(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%     Median    97.5%
 [1,]  0.000000  0.0000000 0.000000
 [2,] -3.025859  0.1497258 1.579292
 [3,] -2.506552  0.6534009 1.996258
 [4,] -3.366026 -0.7995244 4.550954
 [5,] -1.940777  0.3971073 1.492011
 [6,] -4.251821 -1.4007510 3.480677
 [7,] -7.661620 -1.5742313 7.100768
 [8,] -7.131790 -0.7340725 6.415300
 [9,] -5.771472 -0.1045928 4.672834
[10,] -5.035580 -0.4333581 6.998727
[11,] -3.915270 -1.3041734 6.782042

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