Pipeline Extension for Live Trading

Automated stock screener scanning 3,800+ stocks daily for confirmed Stage 2 uptrends passing 8 strict criteria. Features: smart caching (74% fewer API calls), market regime filtering, automated stop-loss calculation, and GitHub Actions automation. Follows Mark Minervini's Trend Template.

A Benchmark Dataset for Multimodal Scientific Fact Checking

Gathered, cleaned and transformed stock price, balance sheet, income and cash flow statements data for 629 companies. Built a neural network to forecast stock prices based on the companies’ fundamental data for a 1-year investment horizon

Script that downloads intraday (past 5 days), daily (past 5 years) and active calls/puts of publicly traded companies.

Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data. Then used Yahoo Finance to get the related stock data and displayed them in the form of charts.

Welcome to Stock Contender – an AI-powered tool designed to assist your market analysis. This tool is not an investment advisor and does not guarantee profits. Invest at your own risk. Stay updated with my latest developments.

Financial Data Processing & Portfolio Analysis - Stock Price Data Integration, Stock Volatility & Portfolio Analysis

Multi-agent AI platform for global equity research, quantitative risk analytics, sentiment modeling, and portfolio intelligence using Gemini 2.0 and Streamlit.

Private Financial Database and Libraries

txn-harvester extracts and structures financial transaction data from unstructured text, parsing amounts, dates, and categories for automation.

Python-based market analytics and data workflow lab for exchange rates, financial metrics, dashboards, and future AI-assisted monitoring.

Automated Stock Scanner analyzes historical stock data to identify lifetime highs, test support levels, and track price appreciation using Python and Yahoo Finance API. Ideal for traders seeking technical insights. 🚀

The financial data analytics and forecasting model analyzes historical financial data to predict future trends and market movements. It uses machine learning algorithms and time series analysis to provide insights for informed decision-making. The model helps improve financial planning and risk management.

Institutional-grade Quantitative Trading Bot for Telegram. Features RAG-based user memory, Microsoft Qlib ML signal generation (Alpha158), and a real-time asynchronous alert engine. Built with Python 3.11, PyTorch, and OpenAI.

Production-style data pipeline for stock prices with PostgreSQL, analytics, and visualization

Automated financial analysis tool for viewing price history, calculating log returns, rolling volatility, and asset correlations using Python with YFinance, Pandas, Matplotlib, and Seaborn.

Tebiz Data API — примеры кода: бухотчётность (ФНС), госзакупки 44-ФЗ, MCP / Russian company data API examples

Fault-tolerant ETL pipeline parsing DART filings into AI readiness scores for enterprise GTM targeting

VectorBT is a set of backtesting and trading tools for financial markets, written in Python. It lets you write and test trading strategies in just a few lines o