view_on_rank: Views on Relative Performance

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

Views on Relative Performance

Description

Helper to construct views on relative performance of assets.

Usage

view_on_rank(x, rank)

## Default S3 method:
view_on_rank(x, rank)

## S3 method for class 'matrix'
view_on_rank(x, rank)

## S3 method for class 'xts'
view_on_rank(x, rank)

## S3 method for class 'tbl_df'
view_on_rank(x, rank)

Arguments

x	An univariate or a multivariate distribution.
rank	A integer with the assets rank (from the worst to the best performer).

Details

If rank = c(2, 1) it is implied that asset in the first column will outperform the asset in the second column. For longer vectors the interpretation is the same: assets on the right will outperform assets on the left.

Value

A list of the view class.

Examples

library(ggplot2)

# Invariants
x <- diff(log(EuStockMarkets))
prior <- rep(1 / nrow(x), nrow(x))

# asset in the first col will outperform the asset in the second col (DAX will
# outperform SMI).
views <- view_on_rank(x = x, rank = c(2, 1))
views

ep <- entropy_pooling(p = prior, A = views$A, b = views$b, solver = "nloptr")
autoplot(ep)

# Prior Returns (SMI > DAX)
colMeans(x)[1:2]

# Posterior Returns (DAX > SMI)
ffp_moments(x, ep)$mu[1:2]

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