smq/directoryAn evolving quant resource archive
Back to directoryResource
Paper / 2025SMQ / 113414724432373
Identifying Risk Variables From Raw ESG Data Using Its Hierarchical Structure
Ionut Florescu / Zachary Feinstein / Zhi Chen
esgResource overview

Identifying Risk Variables From Raw ESG Data Using Its Hierarchical Structure

Paper2025

by Ionut Florescu, Zachary Feinstein, Zhi Chen

Tags
esg

Access resource

Open original source Understand this paper

Continue on SelfMadeQuant

Understand this paper

Suggested foundations for risk measurement and stress. Specialist prerequisites vary by paper.

Before you read

  1. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  2. Expected Shortfall and Other Tail Risk Measures

    Distinguish a loss quantile from the average loss in the tail.

Go further

  1. VaR Estimation in Practice: Variance-Covariance, Historical Simulation, Monte Carlo

    Compare risk estimators and their assumptions.

  2. Backtesting VaR and ES: Coverage Tests and Model Validation

    Check forecasts against realised losses.

Explore a related reading path

Lesson links open public previews. Access to full lessons depends on the topic and your membership.

Explore Quantitative Risk Management

Keep exploring

Related resources

More ideas from similar topics.

6

From the same author

Ionut Florescu, Zachary Feinstein, Zhi Chen

6