ARCApplicationInput: Abnormal Return Calculation Parameters

In EventStudy: Event Study Analysis

Abnormal Return Calculation Parameters

Description

This R6 class defines the parameters for the Return Event Study. We recommend to use the set functionality to setup your Event Study, as we check input parameters.

For more details see the help vignette: vignette("parameters_eventstudy", package = "EventStudy")

Value

a ESTParameters R6 object

Methods

$new()

Constructor for ARCApplicationInput.

$setEMail(eMail)

Set the e-Mail address for reporting. This functionality is currently not working.

$setBenchmarkModel(model = 'mm')

Setter for the benchmark model.s

$setReturnType(returnType)

Setter for the return type (log or simple)

$setTestStatistics(testStatistics)

Setter for the test statistics.

Arguments

ESTARCParameters

An ARCApplicationInput object

eMail

An E-Mail address in String format

model

A benchmark model in String format

returnType

A return type in String format

testStatistics

A String vector with test statistics.

Super classes

EventStudy::ApplicationInputInterface -> EventStudy::EventStudyApplicationInput -> ARCApplicationInput

Public fields

task

Task description

key

Key

benchmark_model

Benchmark model

return_type

Return type

non_trading_days

How to handle non-trading days

test_statistics

Test statistics

request_file

Request file

firm_data

Firm data

market_data

Market data

Methods

Public methods

• ARCApplicationInput$setEMail()

• ARCApplicationInput$setBenchmarkModel()

• ARCApplicationInput$setReturnType()

• ARCApplicationInput$setNonTradingDays()

• ARCApplicationInput$setTestStatistics()

• ARCApplicationInput$setDataFiles()

• ARCApplicationInput$clone()

Inherited methods

• EventStudy::ApplicationInputInterface$serialize()
• EventStudy::ApplicationInputInterface$serializeToJson()
• EventStudy::ApplicationInputInterface$setNamedList()
• EventStudy::ApplicationInputInterface$setResultFileType()
• EventStudy::EventStudyApplicationInput$setup()

---

Method setEMail()

set email

Usage

ARCApplicationInput$setEMail(eMail)

Arguments

eMail

Your E-mail address

---

Method setBenchmarkModel()

set benchmark model

Usage

ARCApplicationInput$setBenchmarkModel(model)

Arguments

model

benchmark model

---

Method setReturnType()

Set return type

Usage

ARCApplicationInput$setReturnType(returnType)

Arguments

returnType

return type

---

Method setNonTradingDays()

Set non trading days

Usage

ARCApplicationInput$setNonTradingDays(nonTradingDays = "later")

Arguments

nonTradingDays

how to handle non traing days

---

Method setTestStatistics()

Set test statistics

Usage

ARCApplicationInput$setTestStatistics(testStatistics = NULL)

Arguments

testStatistics

Test statistic

---

Method setDataFiles()

Set reques, firm, and market data file

Usage

ARCApplicationInput$setDataFiles(
  dataFiles = c(request_file = "01_RequestFile.csv", firm_data = "02_firmData.csv",
    market_data = "03_MarketData.csv")
)

Arguments

dataFiles

Named vector of data files.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ARCApplicationInput$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## Not run: 
# get files for our S&P500 example; 3 files are written in the current 
# working directory
getSP500ExampleFiles()

# Generate a new parameter object
arcParams <- ARCApplicationInput$new()

# set test statistics
arcParams$setBenchmarkModel("garch")

# Setup API object
apiKey <- "{Your API key}"
estSetup <- EventStudyAPI$new()
estSetup$authentication(apiKey)

# Perform Event Study
estSetup$performEventStudy(estParams = arcParams, 
                           dataFiles = c("request_file" = "01_RequestFile.csv",
                                         "firm_data"    = "02_firmData.csv",
                                         "market_data"  = "03_marketData.csv"))

# Download task results and save them in the actiual working directory
estSetup$getTaskResults()

## End(Not run)

EventStudy documentation built on March 31, 2023, 5:43 p.m.