eventstudies (version 1.2.2)

eesDates: Get event list for extreme event study analysis

Description

This function creates event list (clustered and unclustered events) for extreme event study analysis.

Usage

eesDates(input)

Arguments

input

object returned by ‘get.clusters.formatted’

Value

A list object containing:

events.good.normal

‘data.frame’ containing right tail event dates of unclustered events.

events.bad.normal

‘data.frame’ containing left tail event dates of unclustered events.

events.good.purged

‘data.frame’ containing right tail event dates of unclustered events and unclustered events.

events.bad.purged

‘data.frame’ containing left tail event dates of unclustered and clustered events.

Details

The function creates a list of interesting events extracted from the output of get.clusters.formatted. The event list can be directly supplied to the eventstudy function.

It returns extreme right tail and left tail event dates for clustered and unclustered data. The ‘normal’ set consists of event dates for only unclustered events and ‘purged’ set consists of event dates for unclustered and clustered both. Unclustered events consist of clean event window with no event occurring in the event window and clustered events are fused consecutive events which lie in the same tail.

References

Ila Patnaik, Nirvikar Singh and Ajay Shah (2013). Foreign Investors under stress: Evidence from India. International Finance, 16(2), 213-244. http://onlinelibrary.wiley.com/doi/10.1111/j.1468-2362.2013.12032.x/abstract http://macrofinance.nipfp.org.in/releases/PatnaikShahSingh2013_Foreign_Investors.html

Examples

# NOT RUN {
data(OtherReturns)

input <- get.clusters.formatted(event.series = OtherReturns[, "SP500"], 
      	                response.series = OtherReturns[, "NiftyIndex"])

eventlist <- eesDates(input)
str(eventlist, max.level = 2)
# }