dot-fmmc.proc: Implementation of the Factor Model Monte Carlo method.

In braverock/factorAnalytics: Factor Analytics for Asset Return Data

Implementation of the Factor Model Monte Carlo method.

Description

Implementation of the Factor Model Monte Carlo method.

Usage

.fmmc.proc(R, factors, ...)

Arguments

R	single vector of returns
factors	matrix of factor returns
...	allows passing parameters to FactorAnalytics.

Details

Returns a fmmc object that contains the joint empirical density of factors and returns. This fmmc object can be reused to for calculating risk and performance estimates along with standard errors for the estimates

This method takes in data, factors and residual type. It then does the following 1. Fit a time series factor model to the data using user supplied selection and fit variables or it defaults them to stepwise and OLS respectively. If any of the betas are NA then the corresponding factors are dropped 2. If the residual type besides empirical is specified then it fits the corresponding distribution to the residuals and simulates from the fitted distribution. The number of NA's in the simulated sample are the same as original residuals. 3. It then merges factors and non-NA residuals for each asset to create a full outer join of the factors and residuals. We use this joined data to create new simulated returns. Returns together with factors define a joint empirical density.

Author(s)

Rohit Arora

braverock/factorAnalytics documentation built on March 2, 2024, 11:17 p.m.