AntoBr96 / CNN-LSTM_Limit_Order_BookLinks
This notebook contains an independently developed Keras/Tensorflow implementation of the CNN-LSTM model for Limit Order Book forecasting originally proposed by Zhang et al. (https://arxiv.org/pdf/1808.03668.pdf). The current implementation was adopted in the paper written by Briola et al. (https://arxiv.org/pdf/2007.07319.pdf).
☆36Updated 5 years ago
Alternatives and similar repositories for CNN-LSTM_Limit_Order_Book
Users that are interested in CNN-LSTM_Limit_Order_Book are comparing it to the libraries listed below
Sorting:
- Trend Prediction for High Frequency Trading☆43Updated 3 years ago
- Deep learning for limit order book trading and mid-price movement☆56Updated 5 years ago
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆90Updated 4 years ago
- Limit Orderbook CNN model implementation for ETH-BTC (buy-low-sell-high indicator)☆17Updated 2 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆70Updated last year
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆70Updated 2 years ago
- High Frequency Trading Strategies☆48Updated 8 years ago
- High Frequency Jump Prediction Project☆39Updated 5 years ago
- Implementation of "OPTIMAL MARKET MAKING BY REINFORCEMENT LEARNING"☆28Updated 4 years ago
- High-frequency trading in a limit order book☆59Updated 6 years ago
- Example of order book modeling.☆57Updated 6 years ago
- Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm☆15Updated 6 years ago
- Backtest result archive for Momentum Trading Strategies☆64Updated 6 years ago
- ☆19Updated 5 years ago
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆49Updated 10 months ago
- A low frequency statistical arbitrage strategy☆20Updated 6 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
- Mean-Variance Optimization using DL (pytorch)☆32Updated 3 years ago
- 2 algorithms of optimal trade execution: 1) Dynamic Programming 2) Frank-Wolfe Algorithm (Python & C++)☆18Updated 5 years ago
- Some Python codes for explorating High Frequency Data, Generating and Estimating Hawkes Processes and Simulating Limit Order Books.☆50Updated 5 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆29Updated 7 years ago
- This is a research about using ML or RL predictions for HFT Market Making. Backtest was build on Full order log☆31Updated 4 years ago
- These are trading results and arbitrage models from Southern China Center for Statistical Science (SC2S2), Sun Yat-sen University☆22Updated 7 years ago
- Exploring Optimal Order Execution in Simulated Limit Order Books☆19Updated 3 years ago
- Optimizing the Pairs-Trading Strategy using Deep Reinforcement Learning with Trading and Stop-loss Boundaries☆13Updated 3 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆55Updated 2 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
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆92Updated 2 years ago
- Deep learning for price movement prediction using high frequency limit order data☆40Updated 7 years ago
- A project of building and running a trading system according to service oriented architecture standard.☆17Updated 7 years ago