YuxuanXiu / Financial-Time-Series-Trend-Labeling
This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Prediction Based on Trends".
☆40Updated 3 months ago
Alternatives and similar repositories for Financial-Time-Series-Trend-Labeling
Users that are interested in Financial-Time-Series-Trend-Labeling are comparing it to the libraries listed below
Sorting:
- Custom Loss functions for asset return prediction with deep learning regression☆34Updated 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…☆13Updated 3 years ago
- Multi Task Learning Time Series Momentum☆21Updated 11 months ago
- ☆51Updated 4 years ago
- Transformer and MultiTransformer layers for stock volatility forecasting purposes☆66Updated 3 years ago
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated 7 months ago
- DATA-AIDED PAIRS TRADING VIA LEARNED KALMAN WITH BOLLINGER BANDS☆34Updated 2 years ago
- ☆19Updated 4 years ago
- detecting regime of financial market☆36Updated 2 years ago
- Exercises in 'Advances in Financial Machine Learning' by Lopez de Prado☆3Updated 2 years ago
- Code to support my Master's thesis☆19Updated last year
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆37Updated last year
- Official Implementation of SimStock : Representation Model for Stock Similarities☆79Updated 11 months ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆80Updated 2 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆63Updated last year
- Meta labeling is a method of determining the size of the bet.☆22Updated 2 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆44Updated last year
- ☆21Updated last year
- Implementation for "Statistical arbitrage in the US equities market" by Marco Avellaneda and Jeong-hyun Lee☆21Updated 6 years ago
- Dynamic lead/lag inference for time series☆16Updated 6 years ago
- Code repository for demos of the article 'Arbitrage-Free Implied Volatility Surface Generation with Variational Autoencoders'.