Skip to main content
Marginal Contributors Risk Decomposition

Granular risk decompositions to help align risk insights with investment processes

A
Written by Adam Patel
Updated over 10 months ago

Overview

Using marginal risk analytics offers deeper insight into the impact on risk from changing a security position size to the portfolio's risk profile. This "bang-for-your-buck" metric is accompanied by the "X-Sigma-Rho" framework, which decomposes risk across intuitive risk drivers — Exposure/weighting, Risk, and Correlation — along with marginal contribution analytics.

Available as a view within Analyze.Assets, the "X-Sigma-Rho" framework calculates marginal contribution, risk & risk contribution, and correlation and is available in absolute (MCAR) and active space (MCTE) — resulting in slightly different analytic interpretations:

Absolute, non-Active

  • Absolute Volatility
    The standalone risk of the asset itself

  • Absolute Correlation
    The correlation of the standalone asset with the portfolio

  • Marginal Contribution
    The expected increase in total risk given an increase in holding of the asset. Also known as Marginal Contribution to Total Risk

  • Risk Contribution
    The contribution to total risk in terms of standard deviation

Relative, Active

  • Relative Volatility
    The active risk of the asset itself against the index

  • Relative Correlation
    The correlation of the asset against the index

  • Relative Marginal Contribution
    The expected increase in active risk given an increase in the active holding of the asset. Also known as Marginal Contribution to Tracking Error

  • Active Risk Contribution
    The contribution to active risk in terms of standard deviation.

For a detailed discussion on X-Sigma-Rho and MCAR vs. MCTE, please see the sources at the bottom of this document.


Using the X-Sigma-Rho Risk Decomposition via API

The API provides options to generate risk decomposition analytics as granular as needed using the methodology most appropriate for one’s investment process:

  • Absolute, non-active
    → no base, attributionMethod: MCAR

  • Relative, active
    → base specified, attributionMethod: MCTE

  • Absolute, active
    → base specified, attributionMethod: MCAR. This option is available via API only, where:

    • Absolute Volatility
      The standalone risk of the asset itself

    • Absolute Correlation

      The correlation of the standalone asset with the index

    • Marginal Contribution
      The expected increase in active risk given an increase in holding of the asset

    • Risk Contribution
      The contribution to active risk in terms of standard deviation. Also known as Marginal Contribution to Active Risk

Risk Contributors

As before, the riskContributors endpoint returns asset level risk decompositions. Historically Omega Point only provided ‘% of Risk’ / ‘% of Active Risk’ on the Total, Specific, and Factor level as a percentage of the total/active risk of the portfolio. Using the exposureRiskCorrelation endpoint, one can now get the % of Risk / % of Active Risk broken down into it’s drivers: Volatility and Correlation, as well as Marginal Contribution.

{
model(id: "AXWW4-MH") {
simulation(
positionSet: {type: PORTFOLIO, id: "portfolio_2017"}
base: {type: INDEX, id: "IDX-SPY"}
from: "2017-06-30"
to: "2017-06-30"
) {
risk {
date
total
}
riskContributors(attributionMethod: MCTE) {
id
total
exposureRiskCorrelation {
volatility
correlation
marginalContribution
riskContribution
}
attribution {
summary {
factors
specific
}
exposureRiskCorrelation {
factors {
volatility
correlation
marginalContribution
riskContribution
}
specific {
volatility
correlation
marginalContribution
riskContribution
}
}
}
}
}
}
}

Grouped Risk Contributors

groupedRiskContributors now supports Absolute and Relative methods for % of Risk and risk contribution on the group level for total, factor, and specific contributions.

{
model(id: "AXWW4-MH") {
simulation(
positionSet: {type: PORTFOLIO, id: "portfolio_2017"}
base: {type: INDEX, id: "IDX-SPY"}
from: "2017-06-30"
to: "2017-06-30"
) {
risk {
date
total
}
groupedRiskContributors(
groupBy: CLASSIFICATION
classificationTier: "SECTOR"
groupById: "GICS"
attributionMethod: MCTE
) {
id
totalPercentEquity
exposureRiskCorrelation {
riskContribution
}
attribution {
summary {
factors
specific
}
exposureRiskCorrelation{
factors{
riskContribution
}
specific{
riskContribution
}
}
}
}
}
}
}


Sources

Jose Menchero and Ben Davis. Risk Contribution is Exposure times Volatility times Correlation: Decomposing Risk Using the X‐Sigma‐Rho Formula. The Journal of Portfolio Management, Winter 2011, pp. 97‐106.

Phil Durand, Kim Jensen, and Jose Menchero. Different Ways to Measure Marginal Contribution to Risk: Demystifying MCAR versus MCTE. MSCI Research Insight, September 2013.

Did this answer your question?