view_on_mean: Views on Expected Returns

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

Views on Expected Returns

Description

Helper to construct views on expected returns.

Usage

view_on_mean(x, mean)

## Default S3 method:
view_on_mean(x, mean)

## S3 method for class 'matrix'
view_on_mean(x, mean)

## S3 method for class 'xts'
view_on_mean(x, mean)

## S3 method for class 'tbl_df'
view_on_mean(x, mean)

Arguments

x	An univariate or a multivariate distribution.
mean	A double for the target location parameter of the series in x.

Value

A list of the view class.

Examples

library(ggplot2)

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

# View on expected returns (here is 2% for each asset)
mean <- rep(0.02, 4)

# Prior probabilities (usually equal weight scheme)
prior <- rep(1 / n, n)

# View
views <- view_on_mean(x = ret, mean = mean)
views

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

# Probabilities are twisted in such a way that the posterior
# `mu` match's exactly with previously stated beliefs
ffp_moments(x = ret, p = ep)$mu

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