Generating Financial Time Series by Matching Random Convolutional Features

Konrad J. Mueller, Nikita Zozoulenko, Ben Wood +2

Generating realistic financial time series is challenging as training data is often limited to a single historical path. With such scarce data, overfitting is hard to avoid, especi…