burden: Calculate burden based on how different learning assumptions...

In PolicyPortfolios: Tools for Managing, Measuring and Visualizing Policy Portfolios

Calculate burden based on how different learning assumptions affect portfolio size

Description

Internal function to calculate a transformation of portfolio size based on a non-regular assumption of how policy learning works at the instrument level. This generates a weighted portfolio size that can be understood as the "burden" of its size.

Usage

burden(M, nI, nT, learning, weight_by = "instrument")

Arguments

M	Matrix with the policy portfolio, where the first dimension contains instruments and the second contains targets.
nI	Integer with the number of Instruments.
nT	Integer with the number of Targets.
learning	The assumption of the decay of learning. It is either "continuous" (arithmetical decay), "steep" (geometrical decay) or "capped" (sudden decay and constant hereafter).
weight_by	By default learning assumptions are done on different instrument levels ("instrument"). But it is also possible to use Target levels when using "target".

Details

- Arithmetical: assumes a continuous learning. - Geometrical: assumes steep learning. - Radical: assumes capped learning.

This contrasts with the regular portfolio size that assumes no learning is produced between policy instruments.

Value

A value of burden (portfolio size using a different learning assumption).

PolicyPortfolios documentation built on March 18, 2022, 5:36 p.m.