FinancialComputingUCL / DRL_for_Active_High_Frequency_TradingLinks
We introduce the first end-to-end Deep Reinforcement Learning based framework for active high frequency trading.
☆71Updated last year
Alternatives and similar repositories for DRL_for_Active_High_Frequency_Trading
Users that are interested in DRL_for_Active_High_Frequency_Trading are comparing it to the libraries listed below
Sorting:
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆86Updated 4 years ago
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆189Updated last year
- mbt_gym is a module which provides a suite of gym environments for training reinforcement learning (RL) agents to solve model-based high-…☆161Updated last year
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio…☆121Updated 2 years ago
- Using tabular and deep reinforcement learning methods to infer optimal market making strategies☆218Updated 2 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆89Updated 2 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆68Updated last year
- ☆204Updated 2 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆124Updated 5 years ago
- This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limi…☆64Updated 2 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆52Updated 2 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
- JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading☆130Updated last month
- Deep learning modelling of orderbooks☆98Updated 4 years ago
- ☆117Updated 7 years ago
- Pair Trading Strategy using Machine Learning written in Python☆120Updated 3 years ago
- differential Sharpe ratio☆34Updated 6 years ago
- LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data. 🤖📈☆105Updated last year
- Notes on Advances in Financial Machine Learning☆80Updated 6 years ago
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆57Updated 2 years ago
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies☆82Updated last year
- ☆127Updated last year
- Limit Order Book data analysis and modeling using LSTM network☆138Updated 6 years ago
- Research Repo (Archive)☆75Updated 4 years ago
- Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning☆144Updated 5 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆67Updated 2 years ago
- Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierar…☆128Updated 2 years ago
- Cryptocurrency Trading with Reinforcement Learning based on Backtrader☆44Updated 8 months ago
- Backtest result archive for Momentum Trading Strategies☆63Updated 6 years ago
- Calibrates microprice model to BitMEX quote data☆58Updated 4 years ago