Linear Factor Model Base — LinearFactorModel • EventStudy

Base class for multi-factor OLS models used in event studies. All factor models (Market Model, Fama-French, Carhart) share the same estimation approach: OLS regression of excess returns on factor returns during the estimation window.

Super class

ModelBase -> LinearFactorModel

Public fields

model_name: Name of the model.
formula: The regression formula.
required_columns: Columns required in the data.
use_hac: Logical. Use HAC (Newey-West) standard errors.
hac_lag: Integer or NULL. Lag truncation for Newey-West.

Methods

`LinearFactorModel$new()`

Create a new LinearFactorModel.

Usage

LinearFactorModel$new(use_hac = FALSE, hac_lag = NULL)

Arguments

use_hac: Logical. Use HAC (Newey-West) standard errors.
hac_lag: Integer or NULL. Lag truncation for Newey-West.

`LinearFactorModel$fit()`

Fit the linear factor model via OLS on the estimation window.

Usage

LinearFactorModel$fit(data_tbl)

Arguments

data_tbl: Data frame or tibble containing the data to fit.

`LinearFactorModel$abnormal_returns()`

Calculate abnormal returns as observed minus predicted.

Usage

LinearFactorModel$abnormal_returns(data_tbl)

Arguments

data_tbl: Data frame or tibble.

`LinearFactorModel$clone()`

The objects of this class are cloneable with this method.

Usage

LinearFactorModel$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.