From ac6b1322cc52d7a23e11b311bac7fcbf0533f656 Mon Sep 17 00:00:00 2001 From: Wilson Freitas Date: Tue, 24 Feb 2026 06:38:17 -0300 Subject: [PATCH] Add new libraries and resources to the Quantitative Finance list --- site/index.qmd | 34 +++++++++++++++++++++++++++++++--- 1 file changed, 31 insertions(+), 3 deletions(-) diff --git a/site/index.qmd b/site/index.qmd index 850cdb8..772c5dd 100644 --- a/site/index.qmd +++ b/site/index.qmd @@ -28,6 +28,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [pymc3](https://docs.pymc.io/) - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano. - [modelx](https://docs.modelx.io/) - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas. - [ArcticDB](https://github.com/man-group/ArcticDB) - High performance datastore for time series and tick data. +- [pmxt](https://github.com/pmxt-dev/pmxt) - The CCXT for prediction markets. A unified API for trading on Polymarket, Kalshi, and more. ### Financial Instruments and Pricing @@ -59,6 +60,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [Kelly-Criterion](https://github.com/deltaray-io/kelly-criterion) - Kelly Criterion implemented in Python to size portfolios based on J. L. Kelly Jr's formula. - [rateslib](https://github.com/attack68/rateslib) - A fixed income library for pricing bonds and bond futures, and derivatives such as IRS, cross-currency and FX swaps. - [fypy](https://github.com/jkirkby3/fypy) - 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. +- [quantra](https://github.com/joseprupi/quantraserver) High-performance pricing engine built on QuantLib. It exposes QuantLib's functionality through gRPC and REST APIs, enabling distributed computations with FlatBuffers serialization. ### Indicators @@ -70,6 +72,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [streaming_indicators](https://github.com/mr-easy/streaming_indicators) - A python library for computing technical analysis indicators on streaming data. ### Trading & Backtesting +- [the0](https://github.com/alexanderwanyoike/the0) - Self-hosted execution engine for algorithmic trading bots. Write strategies in Python, TypeScript, Rust, C++, C#, Scala, or Haskell and deploy with one command. Each bot runs in an isolated container with scheduled or streaming execution. - [skfolio](https://github.com/skfolio/skfolio) - Python library for portfolio optimization built on top of scikit-learn. It provides a unified interface and sklearn compatible tools to build, tune and cross-validate portfolio models. - [Investing algorithm framework](https://github.com/coding-kitties/investing-algorithm-framework) - Framework for developing, backtesting, and deploying automated trading algorithms. - [QSTrader](https://github.com/mhallsmoore/qstrader) - QSTrader backtesting simulation engine. @@ -106,6 +109,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [pyqstrat](https://github.com/abbass2/pyqstrat) - A fast, extensible, transparent python library for backtesting quantitative strategies. - [NowTrade](https://github.com/edouardpoitras/NowTrade) - Python library for backtesting technical/mechanical strategies in the stock and currency markets. - [pinkfish](https://github.com/fja05680/pinkfish) - A backtester and spreadsheet library for security analysis. +- [PRISM-INSIGHT](https://github.com/dragon1086/prism-insight) - AI-powered stock analysis system with 13 specialized agents, automated trading via KIS API, supporting Korean & US markets. - [aat](https://github.com/timkpaine/aat) - Async Algorithmic Trading Engine - [Backtesting.py](https://kernc.github.io/backtesting.py/) - Backtest trading strategies in Python - [catalyst](https://github.com/enigmampc/catalyst) - An Algorithmic Trading Library for Crypto-Assets in Python @@ -150,6 +154,10 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [rust_bt](https://github.com/jensnesten/rust_bt) - A high performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust. - [Gunbot Quant](https://github.com/GuntharDeNiro/gunbot-quant) - Toolkit for quantitative trading analysis. It integrates an advanced market screener, a multi-strategy, multi-asset backtesting engine. Use with built-in GUI or through CLI. - [StrateQueue](https://github.com/StrateQueue/StrateQueue) - An open‑source, broker‑agnostic Python library that lets you seamlessly deploy strategies from any major backtesting engine to live (or paper) trading with zero code changes and built‑in safety controls. +- [Chartscout](https://chartscout.io) - Real-time cryptocurrency chart pattern detection with automated alerts across multiple exchanges +- [DayTradingBench](https://daytradingbench.com) - Live autonomous benchmark that evaluates LLM trading performance on DAX and Nasdaq indices using identical strategies and real-time market data. API access available. +- [CoinTester](https://cointester.io) - No-code crypto backtesting platform with 100+ indicators, AI sentiment signals, and 5+ years of historical data across 1,000+ trading pairs. +- [PythonTradingFramework](https://github.com/JustinGuese/python_tradingbot_framework) ![Github last commit (branch)](https://img.shields.io/github/last-commit/JustinGuese/python_tradingbot_framework/main) - Python algorithmic trading bot framework for Kubernetes: backtesting, hyperparameter optimization, 150+ technical analysis indicators (RSI, MACD, Bollinger Bands, ADX), portfolio management, PostgreSQL integration, Helm deployment, CronJob scheduling. Minimal overhead, production-ready, Yahoo Finance data. ### Risk Analysis @@ -172,7 +180,9 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [fortitudo.tech](https://github.com/fortitudo-tech/fortitudo.tech) - Conditional Value-at-Risk (CVaR) portfolio optimization and Entropy Pooling views / stress-testing in Python. - [Quant Lab Alpha](https://github.com/husainm97/quant-lab-alpha) — Portfolio risk decomposition and Monte Carlo simulation toolkit with factor-based modeling. - [quantitative-finance-tools](https://github.com/omichauhan-lgtm/quantitative-finance-tools) - Library for portfolio optimization (MVO) and rigorous risk metrics (VaR/CVaR). - +- [curistat](https://github.com/moxiespirit/MyClone/tree/main/volatility_platform) - Futures volatility forecasting platform for ES/NQ. Proprietary CVN rating (1-10), regime detection (CRC composite), 8 directional signals, economic event impact analytics. Includes MCP server for AI agent integration. +- [Prop Trader Compass](https://otto-ships.github.io/prop-trader-compass/) - Interactive risk and payout calculator for Futures and CFD traders; features one-time fee firm comparisons. + ### Factor Analysis - [alphalens](https://github.com/quantopian/alphalens) - Performance analysis of predictive alpha factors. @@ -181,6 +191,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants ### Sentiment Analysis - [Asset News Sentiment Analyzer](https://github.com/KVignesh122/AssetNewsSentimentAnalyzer) - Sentiment analysis and report generation package for financial assets and securities utilizing GPT models. +- [Social Stock Sentiment API](https://api.adanos.org/docs) - REST API analyzing Reddit and X/Twitter for stock mentions and sentiment, providing buzz scores, trending stocks, and AI-generated trend explanations. ### Quant Research Environment @@ -207,6 +218,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [pandas_market_calendars](https://github.com/rsheftel/pandas_market_calendars) - Exchange calendars to use with pandas for trading applications. ### Data Sources +- [goMacro.ai](https://gomacro.ai) - AI-powered economic calendar with institutional-grade insights, bull/bear/base case scenario planning for NFP, CPI, PPI and other macro data releases. - [StockAPI](https://stockapi.com.cn) – Free real-time Chinese stock data (REST & WebSocket). - [yfinance](https://github.com/ranaroussi/yfinance) - Yahoo! Finance market data downloader (+faster Pandas Datareader) - [defeatbeta-api](https://github.com/defeat-beta/defeatbeta-api) - An open-source alternative to Yahoo Finance's market data APIs with higher reliability. @@ -222,6 +234,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [wallstreet](https://github.com/mcdallas/wallstreet) - Real time stock and option data. - [stock_extractor](https://github.com/ZachLiuGIS/stock_extractor) - General Purpose Stock Extractors from Online Resources. - [Stockex](https://github.com/cttn/Stockex) - Python wrapper for Yahoo! Finance API. +- [StockAInsights](https://stockainsights.com) - AI-extracted financial statements API covering SEC filings including foreign filers (20-F, 6-K, 40-F), normalized quarterly and annual data from 2014+. - [finsymbols](https://github.com/skillachie/finsymbols) - Obtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ. - [FRB](https://github.com/avelkoski/FRB) - Python Client for FRED® API. - [inquisitor](https://github.com/econdb/inquisitor) - Python Interface to Econdb.com API. @@ -233,8 +246,12 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [ccy](https://github.com/lsbardel/ccy) - Python module for currencies. - [tushare](https://pypi.org/project/tushare/) - A utility for crawling historical and Real-time Quotes data of China stocks. - [jsm](https://pypi.org/project/jsm/) - Get the japanese stock market data. +- [edinet-mcp](https://github.com/ajtgjmdjp/edinet-mcp) - Parse Japanese XBRL financial statements from EDINET with 161 normalized labels, 26 financial metrics, and multi-company screening. +- [estat-mcp](https://github.com/ajtgjmdjp/estat-mcp) - Access Japanese government statistics (e-Stat) covering population, GDP, CPI, labor, and trade data with MCP integration and Polars export. +- [tdnet-disclosure-mcp](https://github.com/ajtgjmdjp/tdnet-disclosure-mcp) - Access Japanese timely disclosures (TDNet) via MCP. Retrieve earnings, dividends, forecasts, buybacks, and other filings for 4,000+ listed companies. No API key required. - [cn_stock_src](https://github.com/jealous/cn_stock_src) - Utility for retrieving basic China stock data from different sources. - [coinmarketcap](https://github.com/barnumbirr/coinmarketcap) - Python API for coinmarketcap. +- [coinpulse](https://github.com/soutone/coinpulse-python) - Python SDK for cryptocurrency portfolio tracking with real-time prices, P/L calculations, and price alerts. Free tier available. - [after-hours](https://github.com/datawrestler/after-hours) - Obtain pre market and after hours stock prices for a given symbol. - [bronto-python](https://pypi.org/project/bronto-python/) - Bronto API Integration for Python. - [pytdx](https://github.com/rainx/pytdx) - Python Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes. @@ -255,6 +272,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [FinanceDataReader](https://github.com/FinanceData/FinanceDataReader) - Open Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks - [pystlouisfed](https://github.com/TomasKoutek/pystlouisfed) - Python client for Federal Reserve Bank of St. Louis API - FRED, ALFRED, GeoFRED and FRASER. - [python-bcb](https://github.com/wilsonfreitas/python-bcb) - Python interface to Brazilian Central Bank web services. +- [brapi.dev](https://brapi.dev/) - Brazilian stock market data API for B3/Bovespa quotes, historical OHLCV, dividends, and fundamentals. - [market-prices](https://github.com/maread99/market_prices) - Create meaningful OHLCV datasets from knowledge of [exchange-calendars](https://github.com/gerrymanoim/exchange_calendars) (works out-the-box with data from Yahoo Finance). - [tardis-python](https://github.com/tardis-dev/tardis-python) - Python interface for Tardis.dev high frequency crypto market data - [lake-api](https://github.com/crypto-lake/lake-api) - Python interface for Crypto Lake high frequency crypto market data @@ -265,12 +283,15 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [FinanceDatabase](https://github.com/JerBouma/FinanceDatabase) - This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets. - [Trading Strategy](https://github.com/tradingstrategy-ai/trading-strategy/) - download price data for decentralised exchanges and lending protocols (DeFi) - [datamule-python](https://github.com/john-friedman/datamule-python) - A package to work with SEC data. Incorporates datamule endpoints. +- [13F Insight](https://13finsight.com/) - Track institutional investor 13F holdings with AI-powered analysis, position change alerts, and filing summaries. - [Earnings Feed](https://earningsfeed.com/api) - Real-time SEC filings, insider trades, and institutional holdings API. - [Financial Data](https://financialdata.net/) - Stock Market and Financial Data API. - [SaxoOpenAPI](https://www.developer.saxo/) - Saxo Bank financial data API. - [fsynth](https://github.com/welcra/fsynth) - Python library for high-fidelity unlimited synthetic financial data generation using Heston Stochastic Volatility and Merton Jump Diffusion. - [fedfred](https://nikhilxsunder.github.io/fedfred/) - FRED & GeoFRED Economic data API with preprocessed dataframe output in pandas/geopandas, polars/polars_st, and dask dataframes/geodataframes. - [edgar-sec](https://nikhilxsunder.github.io/edgar-sec/) - EDGAR Financial data API with preprocessed dataclass outputs. +- [edgartools](https://github.com/dgunning/edgartools) - AI-native SEC EDGAR library with XBRL financials, clean text extraction, 17+ typed forms, and pandas DataFrames. +- [FXMacroData](https://fxmacrodata.com/) - Real-time forex macroeconomic API for all major currency pairs sourced from central bank announcements. ### Excel Integration @@ -292,6 +313,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [finvizfinance](https://github.com/lit26/finvizfinance) - Finviz analysis python library. - [market-analy](https://github.com/maread99/market_analy) - Analysis and interactive charting using [market-prices](https://github.com/maread99/market_prices) and bqplot. - [QuantInvestStrats](https://github.com/ArturSepp/QuantInvestStrats) - Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, analysis of quantitative strategies. +- [rallyplot](https://rallyplot.com) - Fast, GPU-accelerated financial plotting library ## R @@ -412,7 +434,7 @@ date conversion, scaling factor values, and filtering by the specified date. ## Julia -- [CcyConv](https://github.com/bhftbootcamp/CcyConv.jl) - Currency conversion library for Julia +- [CcyConv.jl](https://github.com/bhftbootcamp/CcyConv.jl) - Currency conversion library for Julia - [CryptoExchangeAPIs.jl](https://github.com/bhftbootcamp/CryptoExchangeAPIs.jl) - A Julia library for cryptocurrency exchange APIs - [Fastback.jl](https://github.com/rbeeli/Fastback.jl) - Blazing fast Julia backtester. - [Lucky.jl](https://github.com/oliviermilla/Lucky.jl) - Modular, asynchronous trading engine in pure Julia. @@ -429,7 +451,7 @@ date conversion, scaling factor values, and filtering by the specified date. - [MarketTechnicals.jl](https://github.com/JuliaQuant/MarketTechnicals.jl) - Technical analysis of financial time series on top of TimeSeries. - [MarketData.jl](https://github.com/JuliaQuant/MarketData.jl) - Time series market data. - [OnlineTechnicalIndicators.jl](https://github.com/femtotrader/OnlineTechnicalIndicators.jl) - Julia Technical Analysis Indicators via online algorithms. -- [OnlineTechnicalIndicators](https://github.com/femtotrader/OnlinePortfolioAnalytics.jl) - A Julia quantitative portfolio analytics (risk / performance) via online algorithms. +- [OnlinePortfolioAnalytics.jl](https://github.com/femtotrader/OnlinePortfolioAnalytics.jl) - A Julia quantitative portfolio analytics (risk / performance) via online algorithms. - [OnlineResamplers.jl](https://github.com/femtotrader/OnlineResamplers.jl) - High-performance Julia package for real-time resampling of financial market data. - [RiskPerf.jl](https://github.com/rbeeli/RiskPerf.jl) - Quantitative risk and performance analysis package for financial time series powered by the Julia language. - [TimeFrames.jl](https://github.com/femtotrader/TimeFrames.jl) - A Julia library that defines TimeFrame (essentially for resampling TimeSeries). @@ -456,6 +478,8 @@ date conversion, scaling factor values, and filtering by the specified date. - [orderflow](https://github.com/focus1691/orderflow) - Orderflow trade aggregator for building Footprint Candles from exchange websocket data. - [ccxt](https://github.com/ccxt/ccxt) - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges. - [PENDAX](https://github.com/CompendiumFi/PENDAX-SDK) - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More. +- [pmxt](https://github.com/pmxt-dev/pmxt) - The CCXT for prediction markets. A unified API for trading on Polymarket, Kalshi, and more. +- [pmxt](https://github.com/qoery-com/pmxt) - A unified API for accessing prediction market data across multiple exchanges. CCXT for prediction markets. ### Data Visualization @@ -495,6 +519,9 @@ date conversion, scaling factor values, and filtering by the specified date. - [XAD](https://github.com/auto-differentiation/xad) - Automatic Differentation (AAD) Library - [TradeFrame](https://github.com/rburkholder/trade-frame) - C++ 17 based framework/library (with sample applications) for testing options based automated trading ideas using DTN IQ real time data feed and Interactive Brokers (TWS API) for trade execution. Comes with built-in [Option Greeks/IV](https://github.com/rburkholder/trade-frame/tree/master/lib/TFOptions) calculation library. - [Hikyuu](https://github.com/fasiondog/hikyuu) - A base on Python/C++ open source high-performance quant framework for faster analysis and backtesting, contains the complete trading system components for reuse and combination. You can use python or c++ freely. +- [OrderMatchingEngine](https://github.com/PIYUSH-KUMAR1809/order-matching-engine) - A production-grade, lock-free, high-frequency trading matching engine achieving 150M+ orders/sec. +- [rallyplot](https://rallyplot.com) - Fast, GPU-accelerated financial plotting library +- [PandoraTrader](https://github.com/pegasusTrader/PandoraTrader) - A C++ CTP trading framework, with very clear logic ## Frameworks @@ -540,6 +567,7 @@ date conversion, scaling factor values, and filtering by the specified date. - [Auto-Differentiation Website](https://auto-differentiation.github.io/) - Background and resources on Automatic Differentiation (AD) / Adjoint Algorithmic Differentitation (AAD). - [Derman Papers](https://github.com/MarcosCarreira/DermanPapers) - Notebooks that replicate original quantitative finance papers from Emanuel Derman. +- [KeepRule](https://keeprule.com/) - Curated library of decision-making principles and investment wisdom from masters like Buffett and Munger, featuring mental models for better investment thinking. - [ML-Quant](https://www.ml-quant.com/) - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs. - [volatility-trading](https://github.com/jasonstrimpel/volatility-trading) - A complete set of volatility estimators based on Euan Sinclair's Volatility Trading. - [quant](https://github.com/paulperry/quant) - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.