Financial Time Series Prediction Using Deep Learning

Understand

In this work we present a data-driven end-to-end Deep Learning approach for time series prediction, applied to financial time series.

• A Deep Learning scheme is derived to predict the temporal trends of stocks and ETFs in NYSE or NASDAQ.
• Our approach is based on a neural network (NN) that is applied to raw financial data inputs, and is trained to predict the temporal trends of stocks and ETFs.
• In order to handle commission-based trading, we derive an investment strategy that utilizes the probabilistic outputs of the NN, and optimizes the average return.