2020
Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks
ICASSP 2020accepted
Deep learning models are capable of achieving state-of-the-art performance on a wide range of time series analysis tasks. However, their performance crucially depends on the employed normalization scheme, while they are usually unable to efficiently handle non-stationary features without first appro…