vkgnandhu177 / Bayesian-Regression-and-BitcoinLinks
# Bayesian-Regression-to-Predict-Bitcoin-Price-Variations Predicting the price variations of bitcoin, a virtual cryptographic currency. These predictions could be used as the foundation of a bitcoin trading strategy. To make these predictions, we will have to familiarize ourself with a machine learning technique, Bayesian Regression, and impleme…
☆21Updated 7 years ago
Alternatives and similar repositories for Bayesian-Regression-and-Bitcoin
Users that are interested in Bayesian-Regression-and-Bitcoin are comparing it to the libraries listed below
Sorting:
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated 8 months ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆20Updated 9 months ago
- Modelling for price change forecast using High-frequency Trading limit order book dynamics using ML algorithms☆25Updated 7 years ago
- Unsupervised Learning to Market Behavior Forecasting Example☆42Updated 5 years ago
- (Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"☆16Updated 7 years ago
- Predicting a Stock Price Using a Genetic Algorithm☆16Updated 7 years ago
- Advancing in Financial Machine Learning☆16Updated 5 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
- Deep Learning - Neural network (RNN, LSTM & GRU)☆66Updated 6 years ago
- Create a mid-price classifier for limit order books using a CNN and LSTM☆14Updated 5 years ago
- ☆22Updated 5 years ago
- High Frequency Jump Prediction Project☆36Updated 5 years ago
- Stock Prediction with XGBoost: A Technical Indicators' approach☆29Updated 6 years ago
- Stock risk premium prediction via FM/ EXT/ GBDT/ XGB/LBGM. Mengxuan Chen's graduation thesis at WHU.☆14Updated 5 years ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆22Updated 3 years ago
- Machine learning approach to high frequency trading, MLP & RNN used☆22Updated 8 years ago
- Exercises in 'Advances in Financial Machine Learning' by Lopez de Prado☆3Updated 2 years ago
- Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm☆15Updated 6 years ago
- I use the random forest algorithm to forecast mid price dynamic over short time horizon i.e. a few seconds ahead☆27Updated 5 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 4 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 4 years ago
- ☆12Updated 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…☆40Updated 4 months ago
- ☆19Updated 4 years ago
- Trading Strategy on S&P500 with different method (Linear Regression, XGBOOST, LSTM, HMM☆10Updated 5 years ago
- A comprehensive approach for stock trading implemented using Neural Network and Reinforcement Learning separately.☆22Updated 6 years ago
- A model for forecasting stock volatility☆22Updated 8 years ago
- Machine Learning for Trading☆14Updated 6 years ago
- In the high-frequency era of trading, orders of stocks can be executed under a millsecond. The information about the thousands of orders …☆10Updated 9 years ago
- ☆49Updated 8 years ago