matteoprata / LOBCAST
LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data. π€π
β93Updated 8 months ago
Alternatives and similar repositories for LOBCAST:
Users that are interested in LOBCAST are comparing it to the libraries listed below
- This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"β51Updated last year
- Official implementation for AAAI2025: AlphaForge: A Framework to Mine and Dynamically Combine Formulaic Alpha Factorsβ126Updated 4 months ago
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolioβ¦β95Updated 2 years ago
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategiesβ71Updated 11 months ago
- This repo contains some codes and outputs of my implementation of DeepLOB model.β80Updated 3 years ago
- ππ¨ Deep Momentum Networks for Time Series Strategiesβ113Updated 4 years ago
- β78Updated 3 weeks ago
- β191Updated last year
- β25Updated last year
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.β139Updated 8 months ago
- A genetic programming algorithm used for generating alpha factors in the multi-factor investment strategyβ58Updated 4 years ago
- β91Updated 6 months ago
- CS7641 Team projectβ93Updated 4 years ago
- Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.β197Updated 2 years ago
- Pytorch implementation of TransLOB from Transformer for limit order booksβ19Updated last year
- Using tabular and deep reinforcement learning methods to infer optimal market making strategiesβ175Updated last year
- Code base for the meta-labeling papers published with the Journal of Financial Data Scienceβ78Updated last year
- This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limiβ¦β53Updated last year
- Notes on Advances in Financial Machine Learningβ75Updated 6 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.β37Updated last year
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'β50Updated last year
- β69Updated 4 years ago
- Reimplementation of Paper: (Re-)Imag(in)ing Price Trendsβ51Updated 5 months ago
- Fintech literature, including journal, conference, book and useful linksβ90Updated 2 years ago
- StockFormer: A Swing Trading Strategy Based on STL Decomposition and Self-Attention Networksβ96Updated 8 months ago
- High Frequency Analysis Based On Level-2 DataοΌLimit Order Book& Transaction Data)β94Updated 8 months ago
- β45Updated 3 years ago
- Official Implementation of SimStock : Representation Model for Stock Similaritiesβ73Updated 7 months ago
- mbt_gym is a module which provides a suite of gym environments for training reinforcement learning (RL) agents to solve model-based high-β¦β156Updated last year
- A study on volume-price factor stock selection model based on wavelet transform and multitask self-attention networkβ55Updated 7 months ago