📄 Executive Summary

This project develops a Python-based environmental risk analytics framework to estimate an investment portfolio's exposure to carbon transition risk and water scarcity risk. While most ESG portfolio models focus primarily on carbon emissions, this analysis introduces a dual-risk framework that integrates both carbon intensity and water stress exposure.

Using portfolio allocation data combined with sector-level environmental intensity metrics, the model identifies which sectors and companies contribute most to sustainability-related risk and evaluates how portfolio rebalancing can reduce environmental exposure.

The analysis highlights that water-related risks are often underrepresented in traditional ESG frameworks, despite being critical for industries such as beverages, agriculture, utilities, and semiconductors.

The project demonstrates how data analytics and environmental metrics can be integrated into portfolio risk analysis to support more sustainable and resilient investment strategies.

💧🌿 Water & Carbon Risk Analytics for Sustainable Investment Portfolios

A Python-based ESG analytics project that estimates an investment portfolio's exposure to climate transition risk and water scarcity risk.

While most ESG portfolio models focus primarily on carbon emissions, this analysis introduces a dual environmental risk framework that also incorporates water stress exposure, an increasingly important sustainability risk for sectors such as beverages, agriculture, utilities, and consumer goods.

📊 Project Overview

Climate change and natural resource scarcity are increasingly recognized as financial risk factors for investors and corporations. As economies transition toward lower-carbon systems and water scarcity intensifies across many regions, investors must understand how these environmental pressures affect their portfolios.

This project evaluates portfolio exposure across two environmental dimensions:

By combining portfolio allocation data with environmental intensity metrics, the analysis identifies which sectors and companies contribute most to environmental risk exposure and explores how portfolio rebalancing can reduce sustainability risk.

💧 Why Water Risk Matters

While carbon emissions dominate most ESG discussions, water scarcity represents a growing environmental and economic risk. Industries such as beverages, agriculture, semiconductors, and utilities depend heavily on reliable water resources, making them particularly vulnerable to regional water stress.

Integrating water-related metrics into portfolio analysis provides a more comprehensive view of environmental exposure and helps investors better understand sustainability risks that traditional carbon-focused frameworks may overlook.

⭐ Key Features

🎯 Project Objectives

  1. Estimate carbon transition risk exposure of an investment portfolio
  2. Measure water stress exposure across sectors and holdings
  3. Identify sectors and companies contributing most to environmental risk
  4. Calculate weighted environmental exposure based on portfolio allocation
  5. Visualise how environmental risk is distributed across the portfolio
  6. Evaluate how portfolio rebalancing can reduce sustainability risk
  7. Demonstrate how ESG data can support more resilient investment decisions

📁 Dataset Description

Portfolio Dataset

Simulated portfolio containing 30 companies across 8 sectors.

ColumnDescription
companyCompany name
sectorIndustry sector classification
portfolio_weightPortfolio allocation weight

Sector Risk Dataset

Sector-level intensity metrics used as proxies for exposure.

ColumnDescription
sectorIndustry sector
carbon_intensityEstimated sector carbon intensity
water_intensityEstimated sector water intensity

Water Stress Dataset

Regional water scarcity indicators used to approximate geographic water risk exposure.

ColumnDescription
regionOperating region
water_stress_indexRegional water scarcity score

Water stress indicators are conceptually based on methodologies developed by the World Resources Institute Aqueduct Water Risk Atlas, a widely used global water risk assessment framework.

Carbon intensity assumptions are inspired by sector emissions insights from organizations such as the International Energy Agency and the CDP environmental disclosure platform.

🔬 Methodology

📐 Key Formulas

Carbon Exposure:
carbon_exposure = portfolio_weight × carbon_intensity
Water Exposure:
water_exposure = portfolio_weight × water_intensity × water_stress_index
Composite ESG Exposure:
composite_esg = carbon_exposure + (0.6 × water_exposure)
Carbon Pricing Scenario:
carbon_cost = carbon_exposure × carbon_price
Water Scarcity Cost Scenario:
water_cost = water_exposure × water_price
Environmental Risk Score:
risk_score = (0.7 × carbon_exposure) + (0.3 × water_exposure)

📈 Visualizations

🛠️ Tools & Technologies

Python Pandas NumPy Matplotlib Jupyter Notebook GitHub Pages HTML / CSS

📂 Project Structure

water-carbon-risk-portfolio-analysis
│
├── data
│   ├── portfolio_data.csv
│   ├── sector_risk.csv
│   └── water_stress.csv
│
├── notebook
│   └── esg_portfolio_analysis.ipynb
│
├── images
│   ├── sector_exposure_chart.png
│   ├── portfolio_allocation.png
│   ├── top_holdings.png
│   ├── rebalancing_comparison.png
│   ├── carbon_water_scatter.png
│   ├── risk_heatmap.png
│   └── risk_contribution.png
│
├── index.html
└── README.md

💡 Key Insights

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