SaiKrishnaAnudeepJ / QuantitativeTrading
Create a Model to predict movement of S&P 500 Index based on Quantitative, Qualitative and Public sentiment factors. • Natural language processing (NLP) is used to derive a variable for Public sentiment. • A Final Model is created using ML techniques like Decision Trees, SVMs, Random Forests, Neural Networks.
☆7Updated 7 years ago
Alternatives and similar repositories for QuantitativeTrading:
Users that are interested in QuantitativeTrading are comparing it to the libraries listed below
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆12Updated 2 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 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…☆13Updated 3 years ago
- ☆17Updated 8 years ago
- A low frequency statistical arbitrage strategy☆19Updated 5 years ago
- Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm☆15Updated 5 years ago
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆65Updated 5 years ago
- Time-Series Momentum Strategies☆10Updated 6 years ago
- Pull price targets from IEXCloud and paper trade on Alpaca 🦙☆12Updated 4 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆25Updated last year
- Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM☆52Updated 4 years ago
- A model for forecasting stock volatility☆22Updated 7 years ago
- Backtesting a simple Buy Low Sell High Strategy☆9Updated 3 years ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆21Updated 3 years ago
- Design your own Trading Strategy☆36Updated 11 months ago
- High Frequency Jump Prediction Project☆35Updated 4 years ago
- A multi-factor stock selection model based on random forest with an average annualized yield of 33.74% from March 2014 to June 2017 when …☆14Updated 5 years ago
- #易经 #道家 #十二生肖 #姓氏堂号子嗣贞节牌坊 #天文历法 #张灯结彩 #农历 #夜观星象 #廿四节气 #算卜 #紫微斗数 #十二时辰 #生辰八字 #命运 #风水 《始祖赢政之子赢家黄氏江夏堂联富•秦谏——大秦赋》 万般皆下品,唯有读书高。🚩🇨🇳🏹🦔中科红旗,…☆45Updated 9 months ago
- World Quant University Capstone Project - Swing Trading☆11Updated 2 years ago
- This is the final project of Statistical Arbitrage course and it aims to apply pairs trading in high frequency data to realize auto-tradi…☆18Updated 6 years ago
- Stock Prediction with XGBoost: A Technical Indicators' approach☆27Updated 6 years ago
- These are trading results and arbitrage models from Southern China Center for Statistical Science (SC2S2), Sun Yat-sen University☆17Updated 6 years ago
- PutPremiumProcessor is a Python option screener with a custom formula to score options based on their risk to reward. I created this to f…☆19Updated 2 years ago
- Using Python and Tushare financial database☆25Updated 9 months ago
- A financial trading method using machine learning.☆58Updated last year
- 基于机器学习的多因子研究框架☆14Updated 4 years ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆20Updated 5 months ago
- Some Quant ideas in Backtrader☆11Updated 3 years ago
- In this work an application of the Triple-Barrier Method and Meta-Labeling techniques is explored with XGBoost for the creation of a sent…☆21Updated 11 months ago