SaiKrishnaAnudeepJ / QuantitativeTradingLinks
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.
☆8Updated 7 years ago
Alternatives and similar repositories for QuantitativeTrading
Users that are interested in QuantitativeTrading are comparing it to the libraries listed below
Sorting:
- Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest N…☆25Updated 5 years ago
- Deep learning models for high-frequency financial data (limited order book)☆19Updated 6 years ago
- Pull price targets from IEXCloud and paper trade on Alpaca 🦙☆12Updated 4 years ago
- Time-Series Momentum Strategies☆12Updated 7 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 …☆16Updated 6 years ago
- Testing trading signals of commodity futures☆17Updated 5 years ago
- Quantitative Finance & Algorithmic Trading in Python course of Udemy☆11Updated 7 years ago
- ☆22Updated 6 years ago
- 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 4 years ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆23Updated 3 years ago
- Some Quant ideas in Backtrader☆12Updated 3 years ago
- A first experiment on how to use deep-value investing strategies to find valuable stocks☆13Updated 3 years ago
- An implementation of a stock market trading bot, which uses Deep Q Learning☆24Updated 2 years ago
- ☆19Updated 8 years ago
- Python implementation of the Three Pass Regression Filter☆14Updated 4 years ago
- select stock automatically, trade manually☆12Updated 4 years ago
- ☆11Updated 2 years ago
- This notebook contains an independently developed Keras/Tensorflow implementation of the CNN-LSTM model for Limit Order Book forecasting …☆34Updated 4 years ago
- Crypto-Options Volatility Surface Calibration and Arbitrage☆14Updated 2 years ago
- A project of building and running a trading system according to service oriented architecture standard.☆15Updated 7 years ago
- Mean-Variance Optimization using DL (pytorch)☆31Updated 3 years ago
- Substantial backtesting of statistical arbitrage pairs trading with crypto-currencies☆22Updated 5 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆65Updated 2 years ago
- A low frequency statistical arbitrage strategy☆20Updated 6 years ago
- This repository is for the code of paper "Automated Cryptocurrency Trading Approach Using Ensemble Deep Reinforcement Learning: Learn to …☆17Updated 10 months ago
- A machine learning pipeline that ingest and process a 20-year historical stock price dataset and try to predict future prices using Light…☆12Updated 4 years ago
- High Frequency Jump Prediction Project☆37Updated 5 years ago
- Using Python and Tushare financial database☆28Updated last year
- Built a trading algorithm in Python for the Tesla stocks returning in 39% higher returns than a simple buy and hold strategy, over a peri…☆18Updated 5 years ago