Awesome Quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance).

Contents

• Numerical Libraries & Data Structures
• Financial Instruments & Pricing
• Technical Indicators
• Trading & Backtesting
• Portfolio Optimization & Risk Analysis
• Factor Analysis
• Sentiment Analysis & Alternative Data
• Time Series Analysis
• Market Data & Data Sources
• Prediction Markets
• Calendars & Market Hours
• Visualization
• Excel & Spreadsheet Integration
• Quant Research Environments
• Cross-Language Frameworks
• Reproducing Works, Training & Books
• Commercial & Proprietary Services
• Related Lists

Numerical Libraries & Data Structures

• numpy - Python - NumPy is the fundamental package for scientific computing with Python. GitHub
• scipy - Python - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. GitHub
• pandas - Python - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. GitHub
• polars - Python - Polars is a blazingly fast DataFrame library for manipulating structured data. GitHub
• quantdsl - Python - Domain specific language for quantitative analytics in finance and trading.
• statistics - Python - Builtin Python library for all basic statistical calculations.
• sympy - Python - SymPy is a Python library for symbolic mathematics. GitHub
• pymc3 - Python - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano. GitHub
• modelx - Python - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas. GitHub
• ArcticDB - Python - High performance datastore for time series and tick data.
• CRNG - Python - Contingency Random Number Generator that produces random numbers with real financial market statistical signatures (fat tails, volatility clustering, kurtosis). Matches 86% of real market metrics vs 14% for NumPy.
• xts - R - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
• data.table - R - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
• sparseEigen - R - Sparse principal component analysis.
• TSdbi - R - Provides a common interface to time series databases.
• tseries - R - Time Series Analysis and Computational Finance.
• zoo - R - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
• tis - R - Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
• tfplot - R - Utilities for simple manipulation and quick plotting of time series data.
• tframe - R - A kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.
• Temporal.jl - Julia - Flexible and efficient time series class & methods.
• DataFrames.jl - Julia - In-memory tabular data in Julia.
• TSFrames.jl - Julia - Handle timeseries data on top of the powerful and mature DataFrames.jl.
• TimeArrays.jl - Julia - Time series handling for Julia.

Financial Instruments & Pricing

• PyQL - Python - QuantLib's Python port.
• pyfin - Python - Basic options pricing in Python. ARCHIVED.
• vollib - Python - vollib is a python library for calculating option prices, implied volatility and greeks.
• py_vollib - Python - vollib Python implementation.
• StochVolModels - Python - Pricing analytics and Monte Carlo simulation for stochastic volatility models, including the log-normal SV model and the Heston model.
• QuantPy - Python - A framework for quantitative finance In python.
• Finance-Python - Python - Python tools for Finance.
• ffn - Python - A financial function library for Python.
• pynance - Python - Lightweight Python library for assembling and analyzing financial data.
• tia - Python - Toolkit for integration and analysis.
• pysabr - Python - SABR model Python implementation.
• FinancePy - Python - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
• gs-quant - Python - Python toolkit for quantitative finance.
• willowtree - Python - Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.
• financial-engineering - Python - Applications of Monte Carlo methods to financial engineering projects, in Python.
• optlib - Python - A library for financial options pricing written in Python.
• tf-quant-finance - Python - High-performance TensorFlow library for quantitative finance.
• Q-Fin - Python - A Python library for mathematical finance.
• Quantsbin - Python - Tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them.
• finoptions - Python - Complete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options.
• pypme - Python - PME (Public Market Equivalent) calculation.
• AbsBox - Python - A Python based library to model cashflow for structured product like Asset-backed securities (ABS) and Mortgage-backed securities (MBS).
• mortgagemath - Python - Cent-accurate mortgage amortization schedules with Decimal arithmetic and published-source validation across six countries.
• Intrinsic-Value-Calculator - Python - A Python tool for quick calculations of a stock's fair value using Discounted Cash Flow analysis.
• Kelly-Criterion - Python - Kelly Criterion implemented in Python to size portfolios based on J. L. Kelly Jr's formula.
• rateslib - Python - A fixed income library for pricing bonds and bond futures, and derivatives such as IRS, cross-currency and FX swaps.
• fypy - Python - 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.
• Pyderivatives - Python - Toolkit for option pricing, implied volatility surfaces, risk-neutral densities, and pricing kernel surfaces with support for advanced models including Heston, Kou, and Bates.
• quantra - Python - High-performance pricing engine built on QuantLib. It exposes QuantLib's functionality through gRPC and REST APIs, enabling distributed com