statistical.factor.model: Statistical Factor Model

In PortfolioAnalytics: Portfolio Analysis, Including Numerical Methods for Optimization of Portfolios

Description

Fit a statistical factor model using Principal Component Analysis (PCA)

Usage

statistical.factor.model(R, k = 1, ...)

Arguments

R	xts of asset returns
k	number of factors to use
...	additional arguments passed to prcomp

Details

The statistical factor model is fitted using prcomp. The factor loadings, factor realizations, and residuals are computed and returned given the number of factors used for the model.

Value

#'

• factor_loadings N x k matrix of factor loadings (i.e. betas)

• factor_realizations m x k matrix of factor realizations

• residuals m x N matrix of model residuals representing idiosyncratic risk factors

Where N is the number of assets, k is the number of factors, and m is the number of observations.

PortfolioAnalytics documentation built on May 1, 2019, 10:56 p.m.