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Emissions-Robust Portfolios

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  • Khizar Qureshi
  • H. Oliver Gao

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 $P^{(m)}_j(r,\lambda)=\bigl(1-\lambda/\lambda_{\max,j}\bigr)^m r$. 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.

Suggested Citation

  • Khizar Qureshi & H. Oliver Gao, 2026. "Emissions-Robust Portfolios," Papers 2601.06507, arXiv.org.
  • Handle: RePEc:arx:papers:2601.06507
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    File URL: http://arxiv.org/pdf/2601.06507
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