A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Indicator Go delivers a rich set of technical analysis indicators, customizable strategies, and a powerful backtesting framework. No dependencies, just pure simplicity. ✨ See how! 👀
Indicator TS delivers a rich set of technical analysis indicators, customizable strategies, and a powerful backtesting framework. No dependencies, just pure simplicity. ✨ See how! 👀
A framework for estimating Basel IV capital requirements.
An Excel integration of OpenGamma Strata.
Jupyter notebook examples using QuantLib.
A .NET implementation of Initial Margin models.
Financial Instruments encoded as Smart Contracts. 💰 🏦 📈 🌷 [Work In Progress]
Smart contracts for implementing complex OTC instruments and related infrastructure
This repository presents an algorithm for analyzing financial instruments based on the correlation coefficient. The algorithm allows to calculate the degree of the relationship.
A portfolio of financial instrument recommendations to the average investor regarding the allocation of one’s capital in constructing the optimal portfolio based on different degrees of risk aversion.
RustQuant is a modular quantitative finance platform built in Rust for financial modeling, market data processing, machine learning, and algorithmic trading. It combines high-performance Rust computation with modern data pipelines for scalable quantitative research and trading systems.
This repository implements a Linear Regression model for predicting prices of financial instruments like stocks, currencies, and cryptocurrencies. It includes data preprocessing, model training, and evaluation using performance metrics like Mean Squared Error and R-squared.
Machine learning process to predict financial instrument prices up to 3 days