GARCH Model

Event study model using GARCH(1,1) for time-varying volatility estimation. Uses the rugarch package to fit a GARCH(1,1) model with a market return regressor in the mean equation during the estimation window. Abnormal returns are computed as the difference between observed returns and the GARCH conditional mean. The time-varying sigma from GARCH can be used for standardized test statistics.

See also

Other eventstudy-models: BHARModel, Carhart4FactorModel, ComparisonPeriodMeanAdjustedModel, DCCGARCHModel, FamaFrench3FactorModel, FamaFrench5FactorModel, LinearFactorModel, LogReturn, MarketAdjustedModel, MarketModel, ModelBase, ReturnCalculation, RollingWindowModel, SimpleReturn, VolatilityModel, VolumeModel

Super class

ModelBase -> GARCHModel

Public fields

model_name

Name of the model.

garch_order

GARCH order as c(p, q). Default c(1,1).

Methods

Public methods

• GARCHModel$fit()

• GARCHModel$abnormal_returns()

• GARCHModel$clone()

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GARCHModel$fit()

Fit the GARCH model on the estimation window.

Usage

GARCHModel$fit(data_tbl)

Arguments

data_tbl

Data frame or tibble with firm_returns, index_returns, estimation_window, event_window columns.

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GARCHModel$abnormal_returns()

Calculate abnormal returns from the GARCH model.

Usage

GARCHModel$abnormal_returns(data_tbl)

Arguments

data_tbl

Data frame or tibble.

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GARCHModel$clone()

The objects of this class are cloneable with this method.

Usage

GARCHModel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.