量化投资入门资料整理：1.多因子股票量化框架开源教程 2.学术界和业界的经典资料收录

An open-source, lightweight, and blazing-fast financial machine learning library built with Numba. Process raw trades, generate advanced bars, features, and labels for quantitative research.

QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance.

Course Website Repo for JOURN 8006: Quantitative Research Methods in Journalism

UNMAINTAINED | R-package providing access to fundamental data and valuation metrics for thousands of publicly traded companies worldwide.

End-to-end RL trading framework with PPO agent, self-attention neural network, custom Gym environment, and advanced backtesting.

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.

A new era of cloud-native quantitative trading covering the complete pipeline of quant research + trading with automation at scale

Real-time forex trading system with modular architecture, multi-timeframe signal generation, GMM-based regime detection, Kelly-based risk management, and CLI tools for backtesting, monitoring, and performance analysis.

This repository contains the code for analyzing LGTBIQ-phobia on Twitter, focusing on Spanish tweets from June 28th (Pride Day) between 2015 and 2024, with a special focus on the impact of Elon Musk's acquisition of the platform. It includes data collection, toxicity classification using the Perspective API, statistical analysis, and visualization

Quantitative research of the Consumer Discretionary sector in the NYSE and NASDAQ exchanges to find an optimal pair of automotive stocks for use in a pairs trading strategy.

Extracted financial data(equity, commodity) via APIs and web scraping. Created technical indicators(MA, MACD, RSI) and conducted fundamental analysis. Designed, backtested and assessed trading strategies to calculate KPIs(Sharpe, Sortino etc.). Implemented ML strategies to achieve full automation

This project investigates the nature of black hole singularities and the fate of an infalling observer. We explore the existence of strong and weak singularities, challenging the prevailing notion of a singularity as an unavoidable annihilation point.

A modular Python toolkit for advanced options pricing, volatility modeling, Greeks computation, and risk analysis. Includes Monte Carlo and Black-Scholes models, machine learning volatility surfaces, and interactive visualizations via Streamlit.

Euro Macromechanica (EMM) Backtesting Ecosystem — EUR/USD M5 quant strategy backtest results across the full retail-broker trading era (since 2001; euro introduced 1999, cash 2002). Baseline 2003–Aug 2025; stress 2001–2002. Integrity: SHA-256, GPG, OTS; live run video proofs. Implemented ~10-15% of the full strategy—minimal yet self-sufficient.

HFT & Stochastic control numerical implementations from "Optimal high frequency trading with limit and market orders" (GUILBAUD & PHAM)

Short Term Alpha Model

QuantHedge-MM implements advanced computational methods for pricing and hedging options in markets with stochastic regime shifts. Built for quants and researchers, it extends Black-Scholes to Markov-modulated models.

Quantitative Research @ EL Capital, Januray - May 2025