xicocaio / its-sentarlLinks
Research project implementation for the ICAIF'21 publication and Master's Thesis. ITS-SentARL => Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach
☆42Updated last year
Alternatives and similar repositories for its-sentarl
Users that are interested in its-sentarl are comparing it to the libraries listed below
Sorting:
- Code relating to the paper - Stock Embeddings: Learning Distributed Representations for Financial Assets☆78Updated 10 months ago
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆58Updated 2 years ago
- Transformer and MultiTransformer layers for stock volatility forecasting purposes☆72Updated 4 years ago
- mbt_gym is a module which provides a suite of gym environments for training reinforcement learning (RL) agents to solve model-based high-…☆163Updated last year
- An open-source framework for reduction of overfitting of DRL agents in Finance☆70Updated 2 years ago
- Artificial-Intelligence-Big-Data-Lab / A-Multi-Layer-and-Multi-Ensembled-Stock-Trader-Using-Deep-Learning-and-Deep-Reinforcement-Learning☆58Updated 5 years ago
- Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierar…☆129Updated 2 years ago
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies☆84Updated last year
- Deep Reinforcement Learning for Portfolio Optimization☆128Updated 5 years ago
- apolanco3225 / Deep-Reinforcement-Learning-for-Optimal-Execution-of-Portfolio-Transactions-using-DDPGPerforming a trading strategy using deep deterministic policy gradients to know when to buy, hold or sell stocks in a virtual environment…☆57Updated 6 years ago
- This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"☆67Updated 2 years ago
- This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limi…☆63Updated 2 years ago
- This is the official repository for the paper TLOB: A Novel Transformer Model with Dual Attention for Stock Price Trend Prediction with L…☆81Updated 5 months ago
- sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinfo…☆50Updated 3 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 9 months ago
- This project is part of my internship at ULiege on Deep RL in stock market trading☆44Updated last year
- Replication of Time Series Momentum strategy by Moskowtiz, Ooi, Pedersen, 2011.☆67Updated 4 months ago
- This project implements the two deep reinforcement learning algorithms on portfolio management☆53Updated 7 years ago
- Trading multiple stocks using custom gym environment and custom neural network with StableBaselines3.☆52Updated 2 years ago
- An investment portfolio of stocks is created using Long Short-Term Memory (LSTM) stock price prediction and optimized weights. The perfor…☆34Updated last year
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆69Updated last year
- differential Sharpe ratio☆33Updated 6 years ago
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆38Updated 2 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆53Updated 2 years ago
- Cryptocurrency Trading with Reinforcement Learning based on Backtrader☆45Updated 9 months ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆124Updated 5 years ago
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆87Updated 4 years ago
- Source code for paper:Multi-agent reinforcement learning for liquidation strategy analysis☆58Updated 6 years ago
- A repository for simulating limit order book dynamics from historical data and using it to train a reinforcement learning agent to make m…☆32Updated 2 years ago
- Deep Q-Learning Applied to Algorithmic Trading☆28Updated 4 months ago