lob-deep-learning
Unverified ML strategy on Multi by Jeonghwan-Cheon. BotFinder score 18 out of 100.
Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.
Source: github
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lob-deep-learning
LOBster LOBster is a project entitled , which is end-to-end machine learning pipeline to predict future mid-price using limit order book. Our project provides a source code of the machine learning pipeline that contains data processing, model training and inference. It contains an implementation of DeepLOB (Zhang, 2018) and our modified model. We also provide an implementation of handling code for FI-2010 (Ntakaris et al., 2017), a publicly available benchmark dataset for mid-price forecasting for limit order book data. In addition, we provide a pre-processing tools for custom raw LOB dataset collected in real market microstructure. The pre-processing tool contains several useful functions, such as down-sampling, normalization and labeling. Lastly, our project provides some modules that test the classification performance of trained model. Specially, it contains a simple market simulator that test whether inference of model works in real market microstructure. It tests the trading performance (i.e. cumulative profits) based of inference on the test set. Problem and challenge Importan
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