Jeonghwan-Cheon/lob-deep-learning
Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.
This project helps financial market participants predict future stock mid-prices using high-frequency trading data. It takes raw Limit Order Book (LOB) data as input and outputs predictions of whether the mid-price will go up, down, or stay stationary within a specific timeframe. Traders, market makers, and regulatory authorities can use these predictions to inform trading strategies, manage inventory risk, or anticipate market instability.
146 stars. No commits in the last 6 months.
Use this if you need to forecast short-term market movements based on detailed order book information to gain an edge in trading or risk management.
Not ideal if you are looking for long-term price predictions or if you only have access to historical price data rather than real-time limit order book data.
Stars
146
Forks
31
Language
Python
License
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Category
Last pushed
Dec 11, 2022
Commits (30d)
0
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