English

Emissions-Robust Portfolios

Mathematical Finance 2026-01-13 v1

Abstract

We study portfolio choice when firm-level emissions intensities are measured with error. We introduce a scope-specific penalty operator that rescales asset payoffs as a smooth function of revenue-normalized emissions intensity. Under payoff homogeneity, unit-scale invariance, mixture linearity, and a curvature semigroup axiom, the operator is unique and has the closed form Pj(m)(r,λ)=(1λ/λmax,j)mrP^{(m)}_j(r,\lambda)=\bigl(1-\lambda/\lambda_{\max,j}\bigr)^m r. Combining this operator with norm- and moment-constrained ambiguity sets yields robust mean-variance and CVaR programs with exact linear and second-order cone reformulations and economically interpretable dual variables. In a U.S. large-cap equity universe with monthly rebalancing and uniform transaction costs, the resulting strategy reduces average Scope~1 emissions intensity by roughly 92\% relative to equal weight while exhibiting no statistically detectable reduction in the Sharpe ratio under block-bootstrap inference and no statistically detectable change in average returns under HAC inference. We report the return-emissions Pareto frontier, sensitivity to robustness and turnover constraints, and uncertainty propagation from multiple imputation of emissions disclosures.

Keywords

Cite

@article{arxiv.2601.06507,
  title  = {Emissions-Robust Portfolios},
  author = {Khizar Qureshi and H. Oliver Gao},
  journal= {arXiv preprint arXiv:2601.06507},
  year   = {2026}
}
R2 v1 2026-07-01T08:58:52.512Z