yangshengaa / dynamic_stock_industry_classificationLinks
Use graph-based analysis to re-classify stocks and to improve Markowitz portfolio optimization
☆19Updated 3 years ago
Alternatives and similar repositories for dynamic_stock_industry_classification
Users that are interested in dynamic_stock_industry_classification are comparing it to the libraries listed below
Sorting:
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆15Updated 4 years ago
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆14Updated 2 years ago
- A Practical Application of Hidden Markov Model to Kalman Filter-Based Pairs Trading☆18Updated 4 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆69Updated 2 years ago
- ☆19Updated 5 years ago
- The course, authored by Prof. Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading)…☆13Updated 7 years ago
- Trend Prediction for High Frequency Trading☆43Updated 2 years ago
- A 50ETF Option Volatility Arbitrage Strategy Based on SABR Model☆25Updated 2 years ago
- This repo contains my reimplementation and improvement of DeepLOB model.☆32Updated 4 years ago
- Replication of Time Series Momentum strategy by Moskowtiz, Ooi, Pedersen, 2011.☆67Updated 5 months ago
- Stock risk premium prediction via FM/ EXT/ GBDT/ XGB/LBGM. Mengxuan Chen's graduation thesis at WHU.☆15Updated 5 years ago
- Attribution and optimisation using a multi-factor equity risk model.☆33Updated last year
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆49Updated 10 months ago
- 1th: Kaggle Jane Street Market Prediction: AE MLP+xgb☆48Updated 3 years ago
- Collection of numerical methods for high frequency data, in Python notebooks☆13Updated 4 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 4 years ago
- The source code for the paper☆24Updated 2 years ago
- This trading strategy deploy the copula model to define the divergence of two correlated asset. The backtesting system is built on backtr…☆22Updated 3 years ago
- ☆12Updated 4 years ago
- Exploring Optimal Order Execution in Simulated Limit Order Books☆19Updated 2 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time …☆22Updated 5 years ago
- A simply framework of researching stock data through LSTM by Tensorflow☆17Updated 6 years ago
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆37Updated 2 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆30Updated 2 years ago
- Risk estimation algorithms☆30Updated 7 years ago
- 📈This repo describes a framework that leverages sentiment stability of a financial 10-K report as the trading signal (alpha factor)☆11Updated 4 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆29Updated 7 years ago
- Image Classification for Trading Strategies - Project for Machine Learning Class☆38Updated 4 years ago
- My first high-frequency trading strategy using machine learning☆19Updated 3 years ago