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🌱 Green Thumb: AI-Driven Clean Energy Investment Platform

Green Thumb is an AI-powered investment platform designed to democratize access to high-quality financial data and actionable insights for retail investors—especially those interested in clean energy and nuclear sectors.

By integrating machine learning, sentiment analysis, and advanced financial modeling, Green Thumb delivers:
Comprehensive stock profiles
Personalized investment strategies
Macro outlook reports tailored to the evolving clean energy landscape


Table of Contents


Overview

Green Thumb leverages multiple data sources such as Yahoo Finance, Polygon.io, government regulatory data, and macroeconomic reports to generate:

  • Detailed financial profiles
  • Technical analysis charts
  • AI-generated reports on stocks and ETFs in the clean energy space

It also performs sentiment analysis from financial news and regulatory announcements to provide forward-looking insights.


Features

Stock & ETF Profiles

  • Company financials (Balance Sheet, Income Statement, Cash Flows)
  • AI-generated reports combining historical data, metrics, and market sentiment
  • Interactive charts for stock price trends over multiple time horizons

Investment Strategy

  • Personalized strategies based on user risk tolerance
  • Stock ranking system using sentiment scores, financial ratios & technical indicators

Macro Outlook

  • Energy sector macro reports, integrating policy updates and regulatory shifts
  • Real-time regulatory news analysis affecting clean & nuclear energy

User Experience

  • Modern UI (React + Material-UI + Recharts)
  • Global user context stores preferences like risk tolerance
  • Easy navigation (Sidebar with Account, ETFs, Top Performers, Macro Reports, Strategy)

Problem Statement & Background

Problem Statement

Enhancing Investment Strategies in Clean Energy Amid Regulatory Uncertainty

The clean energy sector faces uncertainty due to:

  • Shifting government policies
  • Fluctuating subsidies
  • Evolving environmental mandates

Traditional investment analysis often overlooks regulatory shifts and investor sentiment. Green Thumb bridges this gap by providing:
✔️ Data-driven AI-powered insights
✔️ Comprehensive financial + qualitative analysis
✔️ Objective, transparent stock recommendations

Background

  • The clean energy sector (solar, wind, nuclear, hydrogen) is at a critical juncture.
  • Retail investors struggle with access to institutional-grade analysis tools.
  • Green Thumb’s approach: AI-powered financial modeling, sentiment analysis, and policy tracking.

Data Sources

Stock & ETF Data:

Macro & Regulatory Data:

  • U.S. Energy Information Administration (EIA)
  • International Renewable Energy Agency (IRENA)
  • Kaggle datasets on energy markets

News & Sentiment Analysis:

  • Reuters, CNBC, Bloomberg, Seeking Alpha
  • Government filings & regulatory updates
  • Custom NLP web scrapers for macro news

Project Architecture

Backend (Flask)

  • API server for stock data, sentiment analysis & macro reports
  • ML integration with OpenAI & FinBERT for AI-generated insights
  • Third-party APIs: Yahoo Finance, Polygon.io, OpenAI

Frontend (React)

  • Built with React + Material-UI + Recharts
  • Real-time financial charts with smooth UI/UX
  • Global state management using React Context API

Setup & Installation

Backend Setup (Flask)

# Clone the repository
git clone https://github.com/yourusername/GreenThumb.git
cd GreenThumb

# Set up virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Configure API keys (create a .env file)
echo "OPENAI_API_KEY=your_openai_api_key" >> .env
echo "POLYGON_API_KEY=your_polygon_api_key" >> .env

# Start the backend server
python app.py

Backend Setup (Flask)

cd frontend/hackathon-dashboard

# Install dependencies
npm install

# Start the development server
npm start

Contributors

Simran Sharma (simisharma14), Jeslyn Guo (jeslyn-guo), Andrew Verzino (drewverzino), Chloe Nicola (chloen3).

Acknowledgements

A special thanks to all those working toward making clean energy investments accessible and data-driven. A special thanks to the organizers of Hacklytics 2025.

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  • Python 46.3%
  • JavaScript 29.3%
  • CSS 13.3%
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