dreyhsu / Meta_LabelingLinks
Meta labeling is a method of determining the size of the bet.
☆27Updated 3 years ago
Alternatives and similar repositories for Meta_Labeling
Users that are interested in Meta_Labeling are comparing it to the libraries listed below
Sorting:
- Backtest result archive for Momentum Trading Strategies☆61Updated 6 years ago
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies☆80Updated last year
- Notes on Advances in Financial Machine Learning☆80Updated 6 years ago
- Solutions for selected exercises from Advances in Financial Machine Learning by Marcos Lopez De Prado☆66Updated 2 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆66Updated 2 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆85Updated 2 years ago
- Collection of indicators that I used in my strategies.☆56Updated 4 months ago
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆38Updated last year
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆71Updated 5 years ago
- ☆75Updated last year
- Research Repo (Archive)☆75Updated 4 years ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆68Updated last year
- ☆42Updated 2 years ago
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆47Updated 6 months ago
- In this repository, an event-driven backtester is implemented based on QuantStart articles. The backtester is programmed in Python featur…☆66Updated 4 years ago
- ☆40Updated 4 years ago
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆58Updated 2 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆125Updated 5 years ago
- An expansion of the Triple-Barrier Method by Marcos López de Prado☆41Updated last year
- A Collection of public tutorials published in the qubitquants.pro blog☆70Updated 2 years ago
- Pair Trading Strategy using Machine Learning written in Python☆119Updated 3 years ago
- To classify trades into buyer- and seller-initiated.☆145Updated 2 years ago
- This Python package manages methods to reshape tick by tick data for order flow analysis☆103Updated last week
- Examples of nautilus script☆37Updated 7 months ago
- Generate various Alternative Bars both historically and at real-time.☆35Updated 2 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆14Updated 4 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆66Updated last year
- A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.☆57Updated last year
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆122Updated last year
- Different quantitative trading models research☆53Updated 7 months ago