This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

Technical Analysis Library using Pandas and Numpy

Transparent and Efficient Financial Analysis

modular quant framework.

Finviz analysis python library.

quant framework for stock

Teaches step-by-step to analysis stock data in python.

A tool that allows you to visually compare the fundamentals of over 6,000 companies.

Find your trading, investing edge using the most advanced web app for technical and fundamental research combined with real time sentiment analysis.

Python program that rates stocks out of 100 based on valuation, profitability, growth, and price performance metrics, relative to the company's sector.

A financial chat application powered by LangChain, OpenBB, and Claude 3 Opus.

Financial pipeline for the data-driven investor to research, develop and deploy robust strategies. Big Data ingestion, risk factor modeling, stock screening, portfolio optimization, and broker API.

FinML: A Practical Machine Learning Framework for Dynamic Stock Selection

Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka

This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it!

Database for crypto data, supporting several exchanges. Can be used for TA, bots, backtest, realtime trading, etc.

A free MCP server to analyze and extract insights from public filings, earnings transcripts, financial metrics, stock market data, private market transactions, and deep web-based research within Claude Desktop and other popular MCP clients.

This repository enables traders/investors to spot undervalued stocks automatically in the market efficiently to help them maximise their profits.

Screen stocks on fundamentals and estimate their intrinsic value

Deep Reinforcement Learning (DRL) stock trading system with LSTM-PPO, integrating technical indicators and FinBERT-based news sentiment analysis.

A Database Management System(DBMS) project on stock market portfolio management system which also consists of scrib suggestion by analyzing fundamental and technical signals.

Scrape and analyse fundamental stock data of Indonesian listed companies. Fetches stock information from IDX, retrieves key statistics using StockBit and YFinance APIs, and stores the results in Google Sheets or local Excel file for easy analysis

C# Wrapper for EOD Historical Data. Financial Data APIs.

Time Series forecasting using Seasonal ARIMA & Prophet. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots to identify Moving average and Auto-regressive order of series. Transformed series to make it stationary.

Python module to interact with TipRanks API.

This is a webapp which predicts stock prices for Indian stock markets(can be used for other stock markets as well) using both fundamental and technical analysis

PyIndicators is a powerful and user-friendly Python library for financial technical analysis indicators, metrics and helper functions for pandas and polars dataframes. Written entirely in Python, it requires no external dependencies, ensuring seamless integration and ease of use.

High-Performance Computing. Fundamental Analysis Stock Screener and Ranker

AI-powered fundamental analysis platform. TimescaleDB, CrewAI agents, portfolio optimization, pair trading, and automated alpha extraction.

Webscrape stock statistic data from: yahoo finance, reuters, morningstar, zacks.