LeonardoBerti00 / TLOBLinks
This is the official repository for the paper TLOB: A Novel Transformer Model with Dual Attention for Stock Price Trend Prediction with Limit Order Book Data.
☆74Updated 3 months ago
Alternatives and similar repositories for TLOB
Users that are interested in TLOB are comparing it to the libraries listed below
Sorting:
- LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data. 🤖📈☆105Updated last year
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆58Updated 2 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆124Updated 5 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆50Updated last year
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆86Updated 4 years ago
- ☆127Updated last year
- ☆106Updated 7 months ago
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆185Updated last year
- Transformers for limit order books☆115Updated 5 years ago
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies☆81Updated last year
- DeepMarket is a framework for performing Limit Order Book simulation with Deep Learning. This is also the official repository for the pap…☆50Updated last month
- Code relating to the paper - Stock Embeddings: Learning Distributed Representations for Financial Assets☆77Updated 8 months ago
- Pytorch implementation of TransLOB from Transformer for limit order books☆26Updated 2 years ago
- ☆37Updated 2 years ago
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio…☆120Updated 2 years ago
- This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"☆66Updated 2 years ago
- ☆203Updated 2 years ago
- ☆32Updated last year
- A study on volume-price factor stock selection model based on wavelet transform and multitask self-attention network☆81Updated 3 months ago
- A deep reinforcement learning framework for generating formulaic alpha factors for quantitative investment, powered by GFlowNet, implemen…☆70Updated 3 months ago
- This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (…☆253Updated 2 years ago
- StockFormer: A Swing Trading Strategy Based on STL Decomposition and Self-Attention Networks☆115Updated last year
- TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative fin…☆47Updated 2 years ago
- We introduce the first end-to-end Deep Reinforcement Learning based framework for active high frequency trading.☆71Updated last year
- Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierar…☆128Updated 2 years ago
- ☆53Updated 4 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆87Updated 2 years ago
- This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limi…☆64Updated 2 years ago
- pseudocode and algorithms for the paper "Alpha$^2$: Discovering Logical Formulaic Alphas using Deep Reinforcement Learning"☆153Updated last year
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆49Updated 7 months ago