FamaMacbeth: Fama MacBeth Cross-Sectional Regressions

In GregoryBrownson/EAPR: Empirical Asset Pricing Research Platform

Description

Computes cross-sectional regressions for each period

Usage

FamaMacbeth(formula, x, type = "ols", outliers.method = "winsorize",
  outliers.level = 0.005, robust.control = NULL)

## S3 method for class 'FamaMacbeth'
summary(x)

## S3 method for class 'FamaMacbeth'
plot(x)

Arguments

formula	An eapr object which contains the time series of variables for all stocks.
x	Either a vector of percentile cut points or the number of quantiles to compute. If the latter, quantiles are computed using evenly spaced percentile cut points.
type	Type(s) of regression method(s) to use. Current supported methods are least-squares and robust MM regressions. Least-squares may be selected by giving this parameter a value 'ols' or 'ls' and Robust MM is chosen by giving this parameter a value of 'mm' or 'robust.mm'.
outliers.method	Method for dealing with outliers. Options are 'trim', 'winzorize', and 'none'.
outliers.level	Level to use for outliers. Indicates that whichever method chosen, unless 'none', will be applied to the x and 1 - x percentiles.
robust.control	Specifies model parameters for robust regression. See lmrobdet.control for more info.

Value

Data.table containing a time series of intercepts and slopes if only one regression method is selected. A list of data.tables if multiple regression methods selected.

Author(s)

Gregory Brownson, [e-mail]

GregoryBrownson/EAPR documentation built on Oct. 28, 2019, 7:27 p.m.