KodAgge / Reinforcement-Learning-for-Market-MakingLinks
Using tabular and deep reinforcement learning methods to infer optimal market making strategies
☆196Updated last year
Alternatives and similar repositories for Reinforcement-Learning-for-Market-Making
Users that are interested in Reinforcement-Learning-for-Market-Making are comparing it to the libraries listed below
Sorting:
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆165Updated last year
- Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.☆223Updated 3 years ago
- This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"☆61Updated 2 years ago
- HFTFramework utilized for research on " A reinforcement learning approach to improve the performance of the Avellaneda-Stoikov market-ma…☆239Updated 3 months ago
- Implementation of HFT backtesting simulator and Stoikov strategy☆123Updated 2 years ago
- High-frequency statistical arbitrage☆196Updated last year
- A collection of homeworks of market microstructure models.☆247Updated 7 years ago
- A project of using machine learning model (tree-based) to predict short-term instrument price up or down in high frequency trading.☆163Updated 5 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-…☆157Updated last year
- Order Imbalance Strategy in High Frequency Trading☆133Updated 7 years ago
- ☆114Updated 7 years ago
- Python code for High-frequency trading in a limit order book by Marco Avellaneda and Sasha Stoikov☆144Updated 5 years ago
- Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning☆140Updated 5 years ago
- CS7641 Team project☆95Updated 4 years ago
- Limit Order Book data analysis and modeling using LSTM network☆136Updated 6 years ago
- experiments with pair trading☆304Updated 6 months ago
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio…☆114Updated 2 years ago
- Pair Trading Strategy using Machine Learning written in Python☆119Updated 3 years ago
- ☆200Updated 2 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆119Updated 5 years ago
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆83Updated 4 years ago
- Volume-Synchronized Probability of Informed Trading☆113Updated 11 years ago
- Avellaneda-Stoikov HFT market making algorithm implementation☆550Updated last year
- ☆138Updated 2 years ago
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆118Updated last year
- High frequency trading (HFT) framework built for futures using machine learning and deep learning techniques☆467Updated 2 years ago
- Collect BinanceFutures's trade and orderbook(depth) feeds.☆103Updated 10 months ago
- Implemented the Avellaneda-Stoikov market-making strategy in an automated trading algorithm. Completed as part of the Optiver Ready Trade…☆77Updated 2 years ago
- ☆398Updated 4 years ago
- To classify trades into buyer- and seller-initiated.☆144Updated 2 years ago