MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

Quant/Algorithm trading resources with an emphasis on Machine Learning

A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

A collection of awesome papers, articles and various resources on credit and credit risk modeling

algorithmic trading using machine learning

🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.

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.

Python library for building financial machine learning models.

It is a Jupyter notebook that compares different trading strategies using technical analysis, machine learning, and deep learning methods.

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A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

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

Pricing Financial Options contracts using LightGBM, Deep Learning, and Support Vector Machines.

Implementations of Genetic Methods for Financial Machine Learning Applications

Financial Machine Learning Repository

Pytorch implementation of TABL from Temporal Attention Augmented Bilinear Network for Financial Time Series Data Analysis

A tool to detect whether numerals present in Financial Texts are in-claim or out-of-claim

실전 금융 머신러닝 완벽 분석 / Advances in Financial Machine Learning

2024학년도 1학기 MLfinLab Project Team repository

Comprehensive analysis of various ML models to detect fraud in financial transactions.

McPortfolio: A Model Context Protocol server providing 9 specialized tools for LLM-driven portfolio optimization using natural language, covering mean-variance to machine learning approaches.

2025학년도 1학기 ML Finance Lab 및 자산운용

A set of financial analytics projects with python.

Two ensemble models made from ensembles of LightGBM and CNN for a multiclass classification problem.

Advanced stock forecasting system using LSTM neural networks with real-time sentiment analysis. Predicts price movements and volatility by combining technical indicators, news sentiment from Finnhub API, and multivariate analysis. Features dual LSTM models, intelligent alerts, and comprehensive risk assessment for informed trading decisions.

QuantifiLib is a modular Python library for event-driven strategy research, developed by Quantifi Sogang. It supports data loading, signal engineering, backtesting, portfolio optimization, time series modeling, and causal inference for systematic finance.

Numerai's Next Top Model

This project implements a financial trading strategy in Julia which nowcast local highs and lows to create trading signals, comparing stable rule set classifiers and gradient boosted tree models for trading performance.

This repository contains the code implementation of the paper titled "Interpretable Deep Learning for Stock Returns: A Consensus-Bottleneck Asset Pricing Model".

An R-package of teaching financial machine learning