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! 👀

Extremely fast quantitative factor cleaning and backtesting library, based on Polars

An easy-to-use manual to use the OpenBB terminal developed by 3 university students

Official public repository of Berlin Quant Lab (BQλ), the quantitative finance initiative of the Berlin Investment Group (BIG). Featuring quantitative finance research, algorithmic trading strategies, market analyses, educational materials, and open-source projects.

DQN stock-trading agent with a custom Gymnasium environment and yfinance data.

A demo for implement of ztsec-xtp-api

Automated paper-trading bot that bets the NO side of overpriced Polymarket temperature markets, using live METAR observations and Open-Meteo forecasts with a Gaussian probability model.

Code for extracting mean-reverting portfolios out of large data sets.

A-Stockit —— 面向 Agent 框架的 A 股量化分析技能库，提供多样化市场操作，无需配置独立 trading bot

🖥️🚀📈📉Algorithmic implementation of automated adjustment of delta hedged initialized short straddle deployed over Derivatives (Options) market

Decision-Aware Risk & Deployment System — a machine learning decision framework for capital deployment and risk posture determination.

Causal discovery pipeline for Bitcoin return drivers — PC Algorithm, NOTEARS, PCMCI, Granger + DoWhy falsification. In partnership with ESILV and Ginjer AM.

MPT portfolio optimizer + parametric VaR, verified via Monte Carlo simulation

A Python client for policyuncertainty.com Economic Policy Uncertainty (EPU) data

Quantitative risk and fraud scoring engine (PD, EL, tiers, governance, FastAPI).

A trading algorithm for Crypto markets, automated and custom methods, utilizing CCXT for multi-plataform usage.

Forecasting 21-day realised volatility on the URA uranium ETF using a stacked LSTM network, benchmarked against a GARCH(1,1) baseline.

Testing SMA crossover trading strategies on S&P 500 stocks using Python

Java-based quantitative stock analysis tool that evaluates historical stock performance, calculates returns, and compares investment trends using financial data.