EDGAR Analytics – Python Library for Extracting, Analyzing, and Forecasting SEC EDGAR Filings. Streamline your financial analysis with comprehensive metrics, growth rates, and automated reporting capabilities.

Comprehensive financial risk analysis toolkit with Altman Z-Score bankruptcy prediction, Value at Risk (VaR) calculations, and historical crisis stress testing. Supports US & European markets with automated company classification.

📈 PydanticAI Stock Assistant - A Python-based financial analysis tool that leverages the Yahoo Finance API (yfinance) to fetch and analyze stock market data. Built with data integrity at its core through Pydantic validation.

🚀 Automate social media content creation and scaling to boost your online presence with this complete, beginner-friendly course.

Finance and Risk Analytics Project: Predicting credit default risk using machine learning models (Logistic Regression, Random Forest) and assessing stock market risk through historical returns and volatility analysis to guide financial risk management and investment strategies.

Euro Macromechanica (EMM) Backtesting Ecosystem — metrics toolkit: methodology schema and metric calculator for the EMM QMI backtest result.

Financial Ratios API provides insights into key financial metrics with data points like Market Capitalization, Earnings Per Share, Price to Earnings Ratio, Debt-to-Equity Ratio and much more.

A full-stack Binance USDT-M Futures trading bot with an interactive React dashboard and a Flask API backend. The system supports market, limit, stop-limit, OCO, TWAP, and grid trading strategies, along with real-time candlestick charts, order book visualization, and WebSocket-based price updates.

📊 Analyze financial risk for stocks and portfolios with real data from Yahoo Finance to make informed investment decisions.

A Python package for quantitative portfolio metrics calculations, including Deflated Sharpe Ratio (DSR)

Designed and implemented an AI financial chatbot in python utilizing advanced NLP and GenAI models to process 10-K/Q documents, achieving 92% accuracy in data extraction and delivering actionable insights with a 30% reduction in analysis time.

This Python toolkit enables SEC data collection and financial data extraction via SEC EDGAR API. It provides 10-K filings download, financial metrics extraction, and batch SEC downloading for investment research tools, quantitative finance, and AI financial analysis.

It is an unguided, real data SQL-based project analyzing movie industry trends. It identifies top movies, industry comparisons, language trends, and studio performance using advanced SQL techniques like joins, aggregates, and views. Key findings include Hollywood's revenue dominance and Kannada movies' top IMDb ratings.