2024학년도 1학기 MLfinLab Project Team repository
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Updated
Sep 10, 2024 - Python
2024학년도 1학기 MLfinLab Project Team repository
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.
Machine Learning based Relation Extraction for Dataset published in paper "FinRED: A Dataset for Relation Extraction in Financial Domain"
An R-package of teaching financial machine learning
Financial Machine Learning Repository
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.
AI for Wealth Management - democratizing wealth management for everyone.
Financial Modelling & Projection and Stock Prices Projection
🪁 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.
A collection of awesome papers, articles and various resources on credit and credit risk modeling
Quantifi Sogang
Using ML and DL to predict price of electricity to help in financial trading in decision making
Causal Factor Investing (Marcos Lopez de Prado, 2023) Workbook
Two ensemble models made from ensembles of LightGBM and CNN for a multiclass classification problem.
Slides for the "Detecting Toxic Flow" paper
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
CatBoost trades bonds in PROD
실전 금융 머신러닝 완벽 분석 / Advances in Financial Machine Learning
Machine Learning for Asset Managers (Lopez de Prado, 2019)
Quant/Algorithm trading resources with an emphasis on Machine Learning
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