Stock Market & Economic Growth Forecasting

Overview

This project forecasts stock market trends, GDP growth, and inflation rates using machine learning models (ARIMA, Monte Carlo Simulation, XGBoost) and real-time economic data from Yahoo Finance, FRED API, and Bloomberg (via Selenium scraping).

Features

• Fetches real-time stock market & economic data via API & web scraping.
• Stores data in SQLite for structured analysis.
• Forecasts stock prices, GDP growth, and inflation trends.
• Generates an interactive visualization dashboard using Streamlit.
• Uses ARIMA & Monte Carlo simulation for financial forecasting.

Project Structure

Stock_Economic_Forecasting/
│-- README.md                 # Project Overview & Instructions
│-- data_collection.py        # Fetches stock, GDP, and inflation data
│-- forecasting_model.py      # Runs ARIMA & ML-based predictions
│-- database.sql              # Stores historical data in SQLite
│-- dashboard.py              # Generates interactive charts & visuals
│-- requirements.txt          # Dependencies for setup

Installation & Setup

1️⃣ Install Dependencies

Run the following command to install required Python libraries:

pip install -r requirements.txt

2️⃣ Run the Data Collection Script

python data_collection.py

This will fetch stock market data, GDP, and inflation rates and store them in SQLite.

3️⃣ Run the Forecasting Model

python forecasting_model.py

This will generate forecasts for stock prices, GDP growth, and inflation.

4️⃣ Run the Interactive Dashboard

streamlit run dashboard.py

This will launch a web-based visualization for interacting with data.

Technologies Used

• Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly, Streamlit)
• APIs (Yahoo Finance, FRED - Federal Reserve)
• Machine Learning (ARIMA, Monte Carlo, XGBoost)
• SQL Database (SQLite for data storage)
• Web Scraping (Selenium & BeautifulSoup for economic news)

Author

Charles Eleri

Next Steps

• Enhance ML models with deep learning (LSTM for time-series).
• Expand API support for crypto market & forex forecasting.
• Deploy the dashboard to AWS or Heroku for public access.

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🔹 GitHub Repo: github.com/charleseleri