view_on_marginal_distribution: Views on Marginal Distribution

In ffp: Fully Flexible Probabilities for Stress Testing and Portfolio Construction

Views on Marginal Distribution

Description

Helper to construct constraints on the marginal distribution.

Usage

view_on_marginal_distribution(x, simul, p)

## Default S3 method:
view_on_marginal_distribution(x, simul, p)

## S3 method for class 'matrix'
view_on_marginal_distribution(x, simul, p)

## S3 method for class 'xts'
view_on_marginal_distribution(x, simul, p)

## S3 method for class 'tbl_df'
view_on_marginal_distribution(x, simul, p)

Arguments

x	An univariate or a multivariate distribution.
simul	An univariate or multivariate simulated panel.
p	An object of the ffp class.

Details

• simul must have the same number of columns than x

• p should have the same number of rows that simul.

Value

A list of the view class.

Examples

set.seed(1)
library(ggplot2)

# Invariants
ret <- diff(log(EuStockMarkets))
n <- nrow(ret)

#' Prior probability distribution
prior <- rep(1 / n, n)

# Simulated marginals
simul <- bootstrap_scenarios(ret, as_ffp(prior), as.double(n))

views <- view_on_marginal_distribution(x = ret, simul = simul, p = prior)
views

ep <- entropy_pooling(p = prior, Aeq = views$Aeq, beq = views$beq, solver = "nlminb")
autoplot(ep)

# location matches
colMeans(simul)
ffp_moments(x = ret, p = ep)$mu

# dispersion matches
cov(simul)
ffp_moments(x = ret, p = ep)$sigma

ffp documentation built on Sept. 29, 2022, 5:10 p.m.