U-CNNpred: A Universal CNN-based Predictor for Stock Markets

Understand

The performance of financial market prediction systems depends heavily on the quality of features it is using.

• While researchers have used various techniques for enhancing the stock specific features, less attention has been paid to extracting features that represent general mechanism of financial markets.
• In this paper, we investigate the importance of extracting such general features in stock market prediction domain and show how it can improve the performance of financial market prediction.
• We present a framework called U-CNNpred, that uses a CNN-based structure.