TimeAggregation: Time Aggregation

In wbach12/p9eventstudy: Eventstudy functions.

Description

This functions aggregates the AR, CAR, SCAR through time and returns the results for the individual events and the time aggregated.

Usage

TimeAggregation(return.data, market.data, model, event.list, event.window,
  estimation.window)

Arguments

return.data	should be a data frame containing dates (Date) in the first column and returns in the rest.
market.data	should be a data frame containing dates (Date) in the first column and market returns in the second.
model	should be a chracter string: "constant-mean-return" or "market"
event.list	should be a data frame created by the MakeEvents function.
event.window	should be a vector of two elements representing the number of observations prior to and after the event date.
estimation.window	is a numeric value representing the number of observations to estimate the normal returns over.

Examples

TimeAggregation(return.data = ReturnData, market.data = MarketData, model = "constant-mean-return",
event.list = EventList, event.window = c(10,10), estimation.window = 90)
TimeAggregation(return.data = ReturnData, market.data = MarketData, model = "market",
event.list = EventList, event.window = c(10,10), estimation.window = 90)

wbach12/p9eventstudy documentation built on May 4, 2019, 7:43 p.m.