KodAgge / Reinforcement-Learning-for-Market-Making
Using tabular and deep reinforcement learning methods to infer optimal market making strategies
☆178Updated 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
- Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.☆198Updated 2 years ago
- Implementation of HFT backtesting simulator and Stoikov strategy☆105Updated last year
- This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"☆53Updated last year
- Python code for High-frequency trading in a limit order book by Marco Avellaneda and Sasha Stoikov☆137Updated 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.☆142Updated 8 months ago
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio…☆98Updated 2 years ago
- A collection of homeworks of market microstructure models.☆221Updated 6 years ago
- algo trading backtesting on BitMEX☆76Updated last year
- High-frequency statistical arbitrage☆165Updated last year
- Order Imbalance Strategy in High Frequency Trading☆128Updated 6 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-…☆158Updated last year
- Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning☆139Updated 5 years ago
- HFTFramework utilized for research on " A reinforcement learning approach to improve the performance of the Avellaneda-Stoikov market-ma…☆223Updated 9 months ago
- CS7641 Team project☆93Updated 4 years ago
- ☆108Updated 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.☆152Updated 5 years ago
- Limit Order Book data analysis and modeling using LSTM network☆135Updated 5 years ago
- ☆191Updated last year
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆102Updated 9 months ago
- To classify trades into buyer- and seller-initiated.☆137Updated 2 years ago
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆82Updated 3 years ago
- Implemented the Avellaneda-Stoikov market-making strategy in an automated trading algorithm. Completed as part of the Optiver Ready Trade…☆69Updated last year
- Personal Project that implements a variety of HFT strategies in C++☆71Updated 3 years ago
- Collect BinanceFutures's trade and orderbook(depth) feeds.☆101Updated 6 months ago
- High Frequency Analysis Based On Level-2 Data（Limit Order Book& Transaction Data)☆95Updated 9 months ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆116Updated 4 years ago
- Collect real-time orderbook, trade and other HFT data from several crypto exchanges using WebSocket connections.☆66Updated 4 years ago
- Volume-Synchronized Probability of Informed Trading☆110Updated 11 years ago
- A bot coded for an algorithmic trading competition using market making, statistical arbitrage, and delta and vega hedging☆70Updated 7 years ago
- experiments with pair trading☆279Updated 2 months ago