On the Structure of Risk Contribution: A Leave-One-Out Decomposition into Inherent and Correlation Risk

TL;DR

This paper introduces a leave-one-out decomposition of risk contribution into inherent and correlation risk, offering clearer diagnostics for portfolio risk analysis and management.

Contribution

It provides a novel, interpretable decomposition of risk contributions within standard RC, enhancing risk diagnostics and understanding of portfolio dynamics.

Findings

Decomposition separates risk into inherent and correlation components.

It maintains strict additivity of risk contributions.

Empirical results show stable, transparent risk diagnostics.

Abstract

This paper develops a decomposition of standard Risk Contribution (RC) into two economically interpretable components: inherent risk and correlation risk. Using a leave-one-out representation, each position's RC separates into a term reflecting its own volatility contribution independent of the portfolio and a term capturing its covariance with the remainder of the portfolio. The inherent component is always positive, arising from the intrinsic volatility of the position, while the correlation component may amplify or mitigate total portfolio risk depending on how the position moves relative to other holdings. Because the decomposition operates within standard RC, it preserves the property of strict additivity. This separation provides diagnostic insight not visible from aggregate risk contributions alone. It distinguishes whether a position contributes risk because it is volatile in isolation or because it is highly correlated with the rest of the portfolio, and it clarifies when a negatively correlated position functions as an effective hedge. Two approaches to time-series analysis are presented to track how inherent and correlation risk evolve across market regimes, revealing whether changes in portfolio risk during stress periods are driven by volatility shocks, correlation shifts, or both. Empirical illustrations suggest that the decomposition provides stable, transparent, and easily implementable risk diagnostics that can support portfolio risk reporting, stress testing, and performance attribution.