A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
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Updated
May 19, 2024 - Python
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau
The adventures of a non-coder through the financial markets.
Cryptocurrency trading bot, and backtesting framework in julia
A simple lightweight trading framework compatible with Stock, Forex, Crypto... markets
Fcore Is an AI Framework for Financial Markets Analysis (Active Development).
ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.
A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资
Open source quantitative trading 🍊
Interactive Brokers TWS/Gateway API in Swift
A dockerized Jupyter quant research environment.
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
Free, open-source crypto trading bot, automated bitcoin / cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments.
A high-frequency trading and market-making backtesting tool in Python and Rust, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
modular quant framework.
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QUIK# (QUIK Sharp) is the QUIK Lua interface ported to .NET.
Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges
Vanilla and exotic option pricing library to support quantitative R&D. Focus on pricing interesting/useful models and contracts (including and beyond Black-Scholes), as well as calibration of financial models to market data.
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