Agnostic Risk Parity: Taming Known and Unknown-Unknowns

TL;DR

The paper introduces Agnostic Risk Parity, a portfolio strategy that balances known and unknown risks by equalizing risk across principal components, improving diversification and robustness over traditional methods.

Contribution

It proposes a novel, symmetry-based portfolio construction method called Agnostic Risk Parity that minimizes unknown-unknown risks and enhances diversification.

Findings

Agnostic Risk Parity portfolios achieve balanced risk across components.

AGP performs well with trend-following strategies.

The method reduces over-optimistic hedging risks.

Abstract

Markowitz' celebrated optimal portfolio theory generally fails to deliver out-of-sample diversification. In this note, we propose a new portfolio construction strategy based on symmetry arguments only, leading to "Eigenrisk Parity" portfolios that achieve equal realized risk on all the principal components of the covariance matrix. This holds true for any other definition of uncorrelated factors. We then specialize our general formula to the most agnostic case where the indicators of future returns are assumed to be uncorrelated and of equal variance. This "Agnostic Risk Parity" (AGP) portfolio minimizes unknown-unknown risks generated by over-optimistic hedging of the different bets. AGP is shown to fare quite well when applied to standard technical strategies such as trend following.