lorenzolucchese/deepOBs: The Short-Term Predictability of Order Book Markets: A Deep Learning Perspective

The main methods, which we believe could be of use to other researchers, are found in: _dataprocess.py: functions for processing order book data dowloaded from LOBSTER to raw order book, order flow and volume features and the corresponding returns; _datamethods.py: auxiliary functions for processed data; _customdatasets.py: create custom tf.dataset objects to load features and responses into models; model.py: a class to build, train and evaluate deepLOB (Zhang et al., 2019), deepOF (Kolm et al., 2021) and deepVOL as keras.models.Model objects; _MCSresults.py: functions to perform the bootstrap Model Confidence Set (Hansen et al., 2011) procedure on result