ESG Return Attribution
Decompose “ESG works” into explainable components: structural drivers, risk exposures, and noise.
Project Snapshot
Return attribution
Signal vs noise
Risk decomposition
Causal framing
Overview
When an ESG factor correlates with returns, that correlation can come from true causal effects, factor exposures, or statistical artifacts. This project builds an attribution framework to separate sources of return and produce reproducible evidence for what is robust versus what is noise.
What I Built
- A return decomposition workflow that isolates interpretable contribution terms.
- Robustness checks across time windows, industries, and risk-adjustment approaches.
- Deliverable visuals: contribution charts, cumulative effect curves, and uncertainty summaries.
Results (fill in)
- One-line conclusion: under which conditions ESG contributes meaningfully (or not).
- How the story changes after risk adjustment (magnitude / significance / stability).
- The most persuasive figure: place a screenshot here.
Artifacts
- Report / slides: TODO
- Code / notebook: TODO
- Data notes: TODO