jiewwantan / XGBoost_stock_predictionLinks
XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project attempts to predict stock price direction by using the stock's daily data and indicators derived from its daily data as predictors. As such this is a classification problem.
☆45Updated 6 years ago
Alternatives and similar repositories for XGBoost_stock_prediction
Users that are interested in XGBoost_stock_prediction are comparing it to the libraries listed below
Sorting:
- Trend Prediction for High Frequency Trading☆42Updated 3 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆72Updated 2 years ago
- Learn how to research fundamental factors using Pipeline, Alphalens, and Sharadar price and fundamental data.☆16Updated last year
- Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio …☆50Updated 3 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆30Updated 2 years ago
- Pairs Trading with Machine Learning on Distributed Python Platform☆125Updated 3 years ago
- The Implied Volatility Smirk of Individual Option in S&P 500 Shows its Underlying Asset’s Return☆38Updated 5 years ago
- CS7641 Team project☆97Updated 5 years ago
- Here I go through the processing of prototyping a mean reversion trading strategy using statistical concepts, then test it in backtrader.☆73Updated 3 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆30Updated 7 years ago
- Modeling the S&P500 index as a hidden markov model for regime identification and creating a trading algorithm to capitalize on hidden sta…☆39Updated 5 years ago
- Backtest result archive for Momentum Trading Strategies☆65Updated 6 years ago
- The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using t…☆61Updated 4 years ago
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆90Updated 4 years ago
- Notes on Advances in Financial Machine Learning☆83Updated 7 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
- Research Repo (Archive)☆74Updated 5 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆97Updated 2 years ago
- This project studies the intrinsic relationship between the stocks’ multiple factors and the investment value of the stocks listed in Chi…☆91Updated 4 years ago
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆70Updated 5 years ago
- my first factor-stock-selecting backtest function☆22Updated 5 years ago
- This notebook contains an independently developed Keras/Tensorflow implementation of the CNN-LSTM model for Limit Order Book forecasting …☆37Updated 5 years ago
- Mean Reversion Trading Strategy☆29Updated 4 years ago
- ☆25Updated 7 years ago
- ☆25Updated 7 years ago
- Built a practical Multi-Factor Backtesting Framework from scratch based on Huatai Security's(One of China's largest sell side) financial …☆68Updated 3 years ago
- 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
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆70Updated last year
- 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…☆22Updated 4 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆126Updated 5 years ago