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Youth ESG Financial Assistant

Overview

The Youth ESG Financial Assistant is an early-stage project focused on developing a machine learning model to help younger investors—especially students—make smarter, more responsible investment decisions. This tool aims to recommend stock investments based on both financial performance and the user's ESG (Environmental, Social, and Governance) preferences.

We aim to combine:

  • Historical stock market data
  • Public ESG ratings
  • Demographic and spending behavior data
  • Real-time financial data (via APIs like yfinance)

With this, our long-term goal is to create a personalized financial advisor that educates users on smart investing strategies while aligning with their values.


Key Features (Planned)

  • 📊 Stock Recommendations based on historical trends and ESG performance
  • 🌿 ESG Personalization allowing users to set values-driven investment goals
  • 🧠 Educational Insights to help students understand market movements and long-term investing
  • Real-Time Integration using APIs for up-to-date financial information

Current Status

We are currently in the data sourcing and planning phase. Tasks include:

  • Exploring and cleaning ESG and financial datasets
  • Mapping ESG data to company stock data
  • Designing the model architecture for recommendation
  • Evaluating how to handle economic shocks and market volatility

Team

  • Michael
  • Rori
  • Amanda
  • Jamie
  • Yonghan

Useful Datasets (In Review)

ESG Data

Financial & Investment Data


Next Steps

  • Finalize datasets to be used
  • Define initial model scope and architecture
  • Set up data pipelines and begin exploratory data analysis (EDA)

Local Setup Guide

For users who want to work on the project locally, please refer to the following documents:

Stay tuned for updates as we move from planning to development!

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Repo for our AI4ALL Class #3 Project

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