Equal Risk Contribution Depends on the Chosen Risk Measure
Summary
The document asks why an equal risk contribution portfolio built with PortfolioAnalytics does not show equal percentage contributions across its assets. Its example uses a six-asset return series and defines portfolio constraints alongside objectives involving mean return, expected tail loss, and risk budgeting. The optimization uses a differential evolution method, while the risk-budgeting objective also requests minimum concentration.
The key interpretive issue is that equal risk contribution is defined relative to a particular risk measure and optimization setup. A portfolio targeting equal contributions under one measure, such as volatility, need not have equal contributions under expected tail loss. The excerpt does not include the referenced chart or any answer explaining whether the displayed percentages are computed from the same risk measure and objective. As a result, it illustrates a common portfolio-construction question but does not provide enough evidence to diagnose the specific output or establish that the optimization achieved its intended target.
Key ideas
- Equal risk contribution is relative to the risk measure used to define contribution.
- An expected-tail-loss risk budget does not necessarily produce equal contributions under other measures.
- Portfolio constraints and the objective configuration affect the resulting weights.
- The example uses a multi-asset return set and differential evolution optimization.
- The missing chart and solution prevent a definitive diagnosis of the reported contributions.
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Full text
# Equal Risk Contribution in Portfolio Analytics r pkg
# Equal Risk Contribution in Portfolio Analytics r pkg
I am trying to estimate the weights of an equal risk portfolio using the PortfolioAnalytics package in r.
To start with, I have tried to redo the example provided in the portfolio vignette. The code is given below,
```
[![library(PortfolioAnalytics)
library(DEoptim)
library(ROI)
require(ROI.plugin.glpk)
require(ROI.plugin.quadprog)
data(edhec)
R <- edhec\[, 1:6\]
colnames(R) <- c("CA", "CTAG", "DS", "EM", "EQMN", "ED")
funds <- colnames(R)
# Create an initial portfolio object with leverage and box constraints
init <- portfolio.spec(assets=funds)
init <- add.constraint(portfolio=init, type="leverage",
min_sum=0.99, max_sum=1.01)
init <- add.constraint(portfolio=init, type="box", min=0.05, max=0.65)
init$constraints\[\[2\]\]$min <- rep(0, 6)
init$constraints\[\[2\]\]$max <- rep(1, 6)
eq_meanETL <- add.objective(portfolio=init, type="return", name="mean")
eq_meanETL <- add.objective(portfolio=eq_meanETL, type="risk", name="ETL",
arguments=list(p=0.95))
eq_meanETL <- add.objective(portfolio=eq_meanETL, type="risk_budget",
name="ETL", min_concentration=TRUE,
arguments=list(p=0.95))
opt_eq_meanETL <- optimize.portfolio(R=R, portfolio=eq_meanETL,
optimize_method="DEoptim",
search_size=2000,
trace=TRUE, traceDE=5)][1]][1]
```
The risk contribution is given in the image.
My question is why is there a difference in the % risk contribution for all the portfolios. isn't the ERC portfolio produces the same contribution for each of the assets in the portfolio.
Thanks.Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.