# wilsonfreitas/awesome-quant **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/wilsonfreitas-awesome-quant).** 24,291 stars · 3,186 forks · Jupyter Notebook ## Links - GitHub: https://github.com/wilsonfreitas/awesome-quant - Homepage: https://wilsonfreitas.github.io/awesome-quant/ - awesome-repositories: https://awesome-repositories.com/repository/wilsonfreitas-awesome-quant.md ## Topics `algorithmic-trading-engine` `algorithmic-trading-library` `algotrading` `arbitrage-bot` `awesome` `awesome-list` `finance` `finance-api` `financial-data` `financial-instruments` `google-finance` `quant` `quantitative-finance` `quantitative-trading` `stock-data` `technical-analysis` `trading-algorithms` `trading-bot` `trading-strategies` `yahoo-finance` ## Description 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 of statistical model pipelines, allowing for the integration of data preprocessing, mathematical transformation, and predictive modeling. Beyond basic analysis, the collection covers advanced capabilities including event-driven backtesting for strategy validation, portfolio optimization techniques, and market sentiment analysis. It also includes resources for automating spreadsheet workflows and establishing modular data connections to external financial exchanges. ## Tags ### Scientific & Mathematical Computing - [Quantitative Finance & Trading](https://awesome-repositories.com/f/scientific-mathematical-computing/quantitative-finance.md) — Acts as a curated directory of open-source software for financial modeling, backtesting, and quantitative analysis. - [Algorithmic Trading](https://awesome-repositories.com/f/scientific-mathematical-computing/quantitative-finance/algorithmic-trading.md) — Serves as a comprehensive hub for frameworks and models used in algorithmic trading and strategy development. - [Backtesting Engines](https://awesome-repositories.com/f/scientific-mathematical-computing/quantitative-finance/backtesting-engines.md) — Simulates historical market performance of investment strategies to validate logic and assess potential risks. - [Financial Analysis Tools](https://awesome-repositories.com/f/scientific-mathematical-computing/quantitative-finance/financial-analysis-tools.md) — Provides curated collections of software libraries and resources for financial modeling and analysis. ([source](https://wilsonfreitas.github.io/awesome-quant/)) - [Technical Analysis](https://awesome-repositories.com/f/scientific-mathematical-computing/quantitative-finance/technical-analysis.md) — Generates financial market signals and trading rules by applying mathematical algorithms to price and volume data. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [High-Performance Scientific Computing](https://awesome-repositories.com/f/scientific-mathematical-computing/high-performance-execution-environments/scientific-computing-platforms/high-performance-scientific-computing.md) — Applies high-performance data structures and statistical functions to solve complex scientific computing problems. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [Vectorized Array Operations](https://awesome-repositories.com/f/scientific-mathematical-computing/high-performance-execution-environments/scientific-computing-platforms/scientific-computing/vectorized-array-operations.md) — Processes large financial datasets using high-performance array operations and optimized linear algebra libraries. - [Statistical Analysis Libraries](https://awesome-repositories.com/f/scientific-mathematical-computing/research-analysis-workflows/research-and-data-analysis-tools/statistical-analysis-libraries.md) — Offers statistical functions and mathematical algorithms for generating trading signals and computing risk metrics. ### Repository Format - [Awesome List](https://awesome-repositories.com/f/repository-format/awesome-list.md) — A community-curated directory that catalogs and links out to other open-source projects, rather than a standalone tool you run yourself. ### Business & Productivity Software - [Trading Strategy Backtesters](https://awesome-repositories.com/f/business-productivity-software/trading-strategy-backtesters.md) — Simulates historical market performance of investment strategies to validate logic and assess potential risks. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [Derivative Pricing Models](https://awesome-repositories.com/f/business-productivity-software/price-list-management/derivative-pricing-models.md) — Computes option values, implied volatility, and risk metrics using established mathematical models. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [Spreadsheet Automation](https://awesome-repositories.com/f/business-productivity-software/spreadsheet-automation.md) — Embeds custom logic directly into spreadsheet environments to automate data extraction and reporting tasks. - [Spreadsheet Automation Tools](https://awesome-repositories.com/f/business-productivity-software/spreadsheet-automation-tools.md) — Executes custom code within spreadsheets to extract data and generate reports automatically. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) ### Development Tools & Productivity - [Domain-Specific Library Aggregations](https://awesome-repositories.com/f/development-tools-productivity/domain-specific-library-aggregations.md) — Provides curated collections of specialized software libraries and tools for quantitative finance and modeling. ### Artificial Intelligence & ML - [Portfolio Optimization Algorithms](https://awesome-repositories.com/f/artificial-intelligence-ml/portfolio-optimization-algorithms.md) — Constructs and rebalances investment allocations using risk parity or mean-variance techniques. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [Financial Forecasting Models](https://awesome-repositories.com/f/artificial-intelligence-ml/financial-forecasting-models.md) — Predicts future trends in financial datasets by applying autoregressive or machine learning models to historical data. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [Market Sentiment Analyzers](https://awesome-repositories.com/f/artificial-intelligence-ml/market-sentiment-analyzers.md) — Extracts insights from news and social media to gauge market mood and identify potential trading signals. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md)) - [Statistical Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/model-training-pipelines/statistical-pipelines.md) — Chains data preprocessing, mathematical transformation, and predictive modeling steps to generate actionable insights. ### Data & Databases - [Financial Data Connectors](https://awesome-repositories.com/f/data-databases/financial-data-connectors.md) — Standardizes communication with external financial APIs to ingest real-time and historical market data. - [Financial Data Processing](https://awesome-repositories.com/f/data-databases/financial-data-processing.md) — Provides a directory of tools for processing market data and performing statistical financial research. - [Market Data Providers](https://awesome-repositories.com/f/data-databases/market-data-providers.md) — Fetches real-time or historical financial information from external exchanges to ensure current market values. ([source](https://cdn.jsdelivr.net/gh/wilsonfreitas/awesome-quant@master/README.md))