jo-cho / meta_labeling_simplifiedLinks
Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prado.
☆15Updated 4 years ago
Alternatives and similar repositories for meta_labeling_simplified
Users that are interested in meta_labeling_simplified are comparing it to the libraries listed below
Sorting:
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆70Updated 2 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆92Updated 2 years ago
- Different trading strategies based on technical analysis using Ethereum/USD 5-minute bars data☆21Updated 4 years ago
- Trend Prediction for High Frequency Trading☆43Updated 2 years ago
- Notes on Advances in Financial Machine Learning☆82Updated 6 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆69Updated last year
- Backtest result archive for Momentum Trading Strategies☆64Updated 6 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆55Updated 2 years ago
- ☆47Updated 2 years ago
- Mean Reversion Trading Strategy☆29Updated 4 years ago
- Implementation of "OPTIMAL MARKET MAKING BY REINFORCEMENT LEARNING"☆28Updated 4 years ago
- Deep learning for limit order book trading and mid-price movement☆56Updated 5 years ago
- Advancing in Financial Machine Learning☆16Updated 5 years ago
- Pairs Trading with Machine Learning on Distributed Python Platform☆122Updated 3 years ago
- Limit Orderbook CNN model implementation for ETH-BTC (buy-low-sell-high indicator)☆17Updated 2 years ago
- Deep q learning on determining buy/sell signal and placing orders☆50Updated 6 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆30Updated 2 years ago
- This notebook contains an independently developed Keras/Tensorflow implementation of the CNN-LSTM model for Limit Order Book forecasting …☆36Updated 5 years ago
- In this repository, the goal is to predict the tick direction of a stock based on its current order book and trade data. A LSTM Neural Ne…☆21Updated 4 years ago
- Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for …☆35Updated last year
- High Frequency Pairs Trading Based on Statistical Arbitrage (Python)☆103Updated 6 years ago
- Example of order book modeling.☆57Updated 6 years ago
- Having effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management…☆51Updated 5 years ago
- Notebook based on the book "Advances in Financial Machine Learning" by Marcos Lopez de Prado☆126Updated 6 years ago
- Research Repo (Archive)☆75Updated 5 years ago
- A 50ETF Option Volatility Arbitrage Strategy Based on SABR Model☆25Updated 2 years ago
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆59Updated 2 years ago
- High Frequency Trading Strategies☆48Updated 8 years ago
- This is a research about using ML or RL predictions for HFT Market Making. Backtest was build on Full order log☆31Updated 4 years ago
- ☆25Updated 7 years ago