Project Title: ESG-Integrated Portfolio Selection for Tech Companies – An Automated Azure ETL & TOPSIS Ranking Framework
Brief Description:
This project tackles the critical challenge of ESG-aware investment screening, where investors must balance sustainability, financial health, market strength, risk, and public controversy—yet traditional ESG ratings are often fragmented and provider-inconsistent. To address this, we built an automated Azure cloud ETL pipeline that ingests and standardizes multi-source data from SEC EDGAR, XBRL, Alpha Vantage, World Bank, Kaggle, NewsAPI, and Yahoo Finance. The unified dataset feeds into an entropy-weighted TOPSIS model to generate objective company rankings, with an additional controversy penalty adjustment to capture negative news exposure and reputational downside risks.
This framework offers a scalable, transparent decision-support tool for asset managers and sustainability analysts, demonstrating how multi-criteria decision-making (MCDM) can navigate tradeoffs between profitability, responsibility, and risk.
GitHub Repository: https://github.com/dragcom/topsis-esg-portfolio-selection