awesome-quant README

The project's README from github.com/wilsonfreitas/awesome-quant. As one markdown file: README.md.

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

Historical & Archived Projects

awesome-quant (wilsonfreitas/awesome-quant)

algorithmic-trading-engine
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What is this?A curated list of libraries, packages and resources for quants - people doing quantitative finance: pricing, trading, backtesting, risk and market data.
Is this a tool I install, or something I read?It is an index, not software: one README organized by task that links to third-party libraries, books and services. You browse it, then add the libraries you pick to your own code.
What are some well-known libraries on the list?NumPy, SciPy, pandas and Polars in the numerical section; pricing features PyQL (QuantLib's Python port), vollib for option pricing and tf-quant-finance built on TensorFlow.
Does it only cover equities trading?No - besides stocks it spans options and derivatives pricing, fixed income like bonds and swaps, portfolio risk, prediction markets and crypto-related tools.
How big is it, and where do I go from there?Nineteen sections deep, with a Historical and Archived Projects section for outdated tools and a Related Lists section pointing to more curations, so it works as a starting hub.
Size
9.4 MB
Stars
30.2K
Updated
CommitSep 13
Age
11y
Commits · 90 Days