PraAnj / SpatialLOB-Learning-spatial-properties-of-Limit-Order-Book
SpatialLOB is designed for stock price movement prediction by exploiting spatial and temporal properties of the Limit Order books. SpatialLOB consists of a deep network combining CNN and Stacked GRU.
☆9Updated 3 years ago
Alternatives and similar repositories for SpatialLOB-Learning-spatial-properties-of-Limit-Order-Book:
Users that are interested in SpatialLOB-Learning-spatial-properties-of-Limit-Order-Book are comparing it to the libraries listed below
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆22Updated 3 years ago
- Limit Order Book Convolutional Neural Network trading bot☆14Updated 2 years ago
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆12Updated 2 years ago
- MarketGPT: Developing a Pre-trained transformer (GPT) for Modeling Financial Time Series☆12Updated 4 months ago
- Pytorch implementation of DeepLOB-ATT and DeepLOB-Seq2Seq from Multi Horizon Forecasting for Limit Order Books☆11Updated 2 years ago
- This repository is for my master's project, A Survey of Deep Learning Architectures for Algorithmic Cryptocurrency Trading, delivered on …☆9Updated 2 years ago
- A Deep Reinforcement Learning model for high volume and frequency Forex Portfolio Management☆11Updated 2 years ago
- ☆15Updated 2 years ago
- High frequency trading algorithm for Bitmex☆21Updated 4 years ago
- A Deep Reinforcement Learning neural net for an original Multi-Dimensional Pairs Trading strategy is proposed☆21Updated 6 years ago
- Exploring Optimal Order Execution in Simulated Limit Order Books☆16Updated 2 years ago
- Paper: https://arxiv.org/pdf/2008.12275.pdf☆26Updated 4 years ago
- We use an adversarial expert based online learning algorithm to learn the optimal parameters required to maximise wealth trading zero-cos…☆10Updated 4 years ago
- Building a High Frequency Trading Engine with Neural Networks☆12Updated 7 years ago
- Deep Q-Learning Auto Market Maker☆12Updated 3 years ago
- Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market…☆16Updated 3 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 3 years ago
- Market making strategies and scientific papers☆13Updated last year
- Vpin caculation and backtesting☆14Updated 5 years ago
- A project of building and running a trading system according to service oriented architecture standard.☆14Updated 7 years ago
- Limit Orderbook CNN model implementation for ETH-BTC (buy-low-sell-high indicator)☆17Updated 2 years ago
- This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time …☆18Updated 4 years ago
- Backtesting a simple Buy Low Sell High Strategy☆9Updated 3 years ago
- Machine learning model to predict NSE stocks for a year☆20Updated 6 years ago
- ☆16Updated 4 years ago
- Implementation of "OPTIMAL MARKET MAKING BY REINFORCEMENT LEARNING"☆27Updated 3 years ago
- High Frequency Jump Prediction Project☆36Updated 4 years ago
- High Frequency Trading Strategies☆42Updated 7 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
- Source code for the course "Deep Reinforcement Learning for High-Frequency Trading" held at the Ukrainian Catholic University / Czech Tec…☆18Updated 2 years ago