FinancialMachineLearning

2023서강대학교 AI금융 캡스톤디자인 프로젝트를 기점으로 개발이 시작되었습니다. 금융 머신러닝 프로젝트를 위한 다양한 기능을 지원합니다.

import FinancialMachineLearning

주요 기능은 다음과 같습니다.

• Portfolio optimization
• Betting size
• Synthetic data
• Stochastic Process
• Shrinkage
• Distance Metrics; entropy, correlation based distance
• Structural Breaks
• Entropy measure
• Asset Pricing
• Feature Importance (based Bagging Algorithm)
• Volatility estimator

reference

• Advances in Financial Machine Learning (Marcos Lopez de Prado, 2018)
• Machine Learning for Asset Manager (Marcos Lopez de Prado, 2020)
• Causal Factor Investing (Marcos Lopez de Prado, 2023)

finLab

to study some financial market issue, such as Asset allocation, Risk optimization, Asset pricing, Trading Strategies using Machine Learning and Deep Learning.

covering the following topics :

• Sharpe Ratio estimation with Monte Carlo simulation
• Dimension shrinkage with Deep Auto encoder
• Stochastic process Generation using Deep Learning
• Dynamic Asset allocation with Reinforcement Learning
• Explainable Machine Learning and Causal Machine Learning