#计算机科学#Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.
#计算机科学#Using tabular and deep reinforcement learning methods to infer optimal market making strategies
Master Thesis: Limit order placement with Reinforcement Learning
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
#时序数据库#Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'
#区块链#Academic python library that records changes to instances of the limit order book for pairs supported on the coinbase exchange.
#区块链#Deep learning approach for market price prediction, in JAX
#计算机科学#DeepLOB Implementation on Bitcoin Perpetual Data
#计算机科学#MarketGPT: Developing a Pre-trained transformer (GPT) for Modeling Financial Time Series
Create a mid-price classifier for limit order books using a CNN and LSTM
Stock market predictions based on order books.
Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morgan AI Research, 2019)>.
#计算机科学#High-frequency trading (HFT) strategies using Machine Learning Techniques on Full Orderbook Tick Data.
#计算机科学#Pytorch implementation of TABL from Temporal Attention Augmented Bilinear Network for Financial Time Series Data Analysis
Used LSTM in Big Data Challenge competiton hosted by Shaastra IIT Madras. Won the second prize
Various implementations of a limit order book for benchmarking.