30 open-source projects similar to lballabio/quantlib, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best QuantLib alternative.
gs-quant is a quantitative finance library and financial data analytics toolkit. It serves as a framework for analyzing financial data, developing systematic trading strategies, and managing risk exposure for derivative products in global markets. The project provides tools for quantitative financial analysis, quantitative portfolio modeling, and the development of systematic trading strategies. It enables the calculation of risk for derivative products to structure and hedge positions across markets.
quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model
This is a quantitative finance library built on TensorFlow for financial engineering, asset pricing, and risk management. It serves as a financial derivative pricing engine, a model calibration tool, and a hardware-accelerated math library for numerical tasks. The library provides specialized capabilities for pricing financial assets using standard models and American option logic, as well as calibrating pricing models to market data through local volatility. It includes tools for constructing yield curves via bootstrapping algorithms and monotone convex interpolation. The framework covers a
Backtrader is a Python framework designed for the development, backtesting, and live execution of algorithmic trading strategies. It provides a comprehensive environment for quantitative finance, allowing users to simulate trading logic against historical market data or connect directly to brokerage platforms for automated real-time trading. The project distinguishes itself through a unified event-driven architecture that treats backtesting and live trading with the same API. This consistency is supported by a flexible data-feed abstraction layer that normalizes diverse financial sources, ena
This project is a C++ template tutorial and metaprogramming guide. It provides instructional content on using templates to implement generic programming and execute Turing-complete logic during the compilation process. The guide serves as a reference for static type dispatching, substitution failure, and the use of concepts to ensure type safety. It covers methods for selecting function implementations at compile time to eliminate runtime branching. The material addresses compile-time type manipulation, including the transformation of type qualifiers and the use of constraints to prevent inv
JQuantLib is a library for Quantitative Finance written in 100% Java
SymEngine is a fast symbolic manipulation library, written in C++
An efficient C++20 GPU numerical computing library with Python-like syntax
LibTomMath is a free open source portable number theoretic multiple-precision integer library written entirely in C.
tiny recursive descent expression parser, compiler, and evaluation engine for math expressions
MIRACL Cryptographic SDK: Multiprecision Integer and Rational Arithmetic Cryptographic Library is a C software library that is widely regarded by developers as the gold standard open source SDK for elliptic curve cryptography (ECC).
Fast, easy automatic differentiation in C++
linalg.h is a single header, public domain, short vector math library for C++
NumCpp is a C++ framework and numerical computing library that provides a toolkit for multi-dimensional array management and mathematical routines. It functions as a C++ implementation of the NumPy ecosystem, offering a scientific computing framework for managing tensors and performing complex algebraic equations. The project enables high-performance array manipulation within a C++ environment without relying on a Python runtime. It distinguishes itself by providing a NumPy-like interface for executing linear algebra, managing multi-dimensional data structures, and performing numerical proces
a lean linear math library, aimed at graphics programming. Supports vec3, vec4, mat4x4 and quaternions
This project is a header-only C++ library designed for graphics mathematics, providing a comprehensive suite of vector, matrix, and quaternion types. It is built using template metaprogramming to generate mathematical primitives at compile time, eliminating the need for precompiled binary libraries and allowing for direct integration into existing build systems. The library is distinguished by its strict adherence to the OpenGL Shading Language specification, ensuring that mathematical results remain consistent across both CPU and GPU code. It provides specialized utilities for managing float
This project is a quantitative finance library providing implementations of numerical methods for financial engineering. It focuses on derivative pricing, portfolio optimization, stochastic simulation, and volatility calibration. The library includes tools for calculating option values using Monte Carlo simulations, binomial trees, and Fourier inversion. It provides a framework for fitting volatility smiles to market data and a simulation engine for generating asset price paths via geometric Brownian motion and jump-diffusion models. The codebase covers broader numerical analysis capabilitie
The FinanceToolkit is an open-source Python library for quantitative finance that provides a unified framework for financial analysis, asset valuation, and risk management. It serves as a comprehensive platform for computing over 200 financial metrics and ratios, with capabilities spanning financial ratio analysis, fixed income analytics, macroeconomic data aggregation, options pricing, and portfolio risk management. The toolkit distinguishes itself through a modular architecture that separates data retrieval from computation, with stateless engines for financial models like Black-Scholes, GA
This project is a Python quantitative finance library designed for gathering, manipulating, and analyzing stock market data. It provides a suite of tools for quantitative stock analysis, including an equity screening framework for filtering stocks based on technical and fundamental criteria. The library features a machine learning price predictor for classifying stock movements and forecasting future price directions. It also includes a financial technical analysis tool to calculate indicators such as Bollinger Bands, RSI, and MACD, alongside an algorithmic trading simulator for testing portf
FinceptTerminal is a quantitative finance platform and financial engineering library designed for asset valuation, risk management, and fixed-income analytics. It provides a comprehensive suite for algorithmic trading and investment strategy automation, integrating specialized language model agents and node-based workflows to automate market research and alpha generation. The project distinguishes itself with a dedicated game theory analysis engine for calculating Nash equilibria and simulating strategic interactions in competitive markets. It also features a specialized credit risk modeling
Awesome-quant is a curated directory of open-source software libraries and tools designed for quantitative finance, algorithmic trading, and financial data analysis. It serves as a central hub for discovering resources that support the entire lifecycle of financial modeling, from raw data ingestion to complex statistical research. The repository organizes specialized tools into categorized collections, enabling users to identify solutions for high-performance numerical computing, technical indicator calculation, and derivative pricing. It highlights frameworks that facilitate the construction
FundamentalAnalysis is a comprehensive financial analysis library, quantitative finance framework, and macroeconomic data integrator. It provides tools for computing financial ratios, executing corporate health metrics, and pricing derivatives and bonds using mathematical models. The project integrates diverse data streams, including global economic indicators, real-time market quotes, and standardized corporate financial statements. It features a technical analysis engine for generating momentum and volatility indicators, as well as a portfolio performance analyzer for tracking risk-adjusted
Jesse is a Python algorithmic trading framework used for developing, backtesting, and executing quantitative trading strategies. It functions as a trading strategy backtester and a machine learning trading platform, providing an environment to train predictive models on historical market data and deploy them into live strategies. The framework features a standardized crypto exchange connectivity layer that allows for the execution of automated spot and futures trades across multiple cryptocurrency exchanges via an exchange-agnostic interface. It includes a quantitative risk analysis toolset t
This project is an automated trading and agentic workflow platform designed to orchestrate complex financial tasks through state-based graphs. It provides a comprehensive framework for building, deploying, and managing autonomous agents that execute multi-step analytical processes, monitor real-time market conditions, and perform high-speed trade execution. The platform distinguishes itself through a robust agentic plugin ecosystem that integrates directly with popular AI-powered development environments and command-line interfaces. It features a specialized financial analysis engine capable