imTurkey / Market-Making-with-Deep-Reinforcement-Learning-from-Limit-Order-Books
This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"
☆53Updated last year
Alternatives and similar repositories for Market-Making-with-Deep-Reinforcement-Learning-from-Limit-Order-Books:
Users that are interested in Market-Making-with-Deep-Reinforcement-Learning-from-Limit-Order-Books are comparing it to the libraries listed below
- Implementation of HFT backtesting simulator and Stoikov strategy☆105Updated last year
- This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limi…☆54Updated last year
- Calibrates microprice model to BitMEX quote data☆56Updated 3 years ago
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio…☆98Updated 2 years ago
- We introduce the first end-to-end Deep Reinforcement Learning based framework for active high frequency trading.☆63Updated last year
- Using tabular and deep reinforcement learning methods to infer optimal market making strategies☆178Updated last year
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆82Updated 3 years ago
- Limit Order Book data analysis and modeling using LSTM network☆134Updated 5 years ago
- Deep learning for limit order book trading and mid-price movement☆49Updated 4 years ago
- Order Imbalance Strategy in High Frequency Trading☆128Updated 6 years ago
- CS7641 Team project☆93Updated 4 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆56Updated 11 months ago
- Literature survey of order execution strategies implemented in python☆41Updated 4 years ago
- An implementation of Avellaneda-Stoikov market making model after reading the seminal paper☆30Updated 3 years ago
- ☆94Updated 6 months ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆39Updated last year
- A curated list of Quantitative Finance papers.☆46Updated last month
- This is a research about using ML or RL predictions for HFT Market Making. Backtest was build on Full order log☆27Updated 3 years ago
- High Frequency Trading Strategies☆41Updated 7 years ago
- Some Python codes for explorating High Frequency Data, Generating and Estimating Hawkes Processes and Simulating Limit Order Books.☆44Updated 4 years ago
- High-frequency statistical arbitrage☆164Updated last year
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆69Updated 4 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆78Updated last year
- Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.☆197Updated 2 years ago
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies☆74Updated 11 months ago
- ☆108Updated 7 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.☆141Updated 8 months ago
- High Frequency Analysis Based On Level-2 Data（Limit Order Book& Transaction Data)☆95Updated 8 months ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆114Updated 4 years ago
- LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data. 🤖📈☆95Updated 9 months ago