Euclidean Technologies: Deep Learning And Long-Term Investing, Structuring The Data [Part 2]

Part 2: Deep Learning And Long-Term Investing, Structuring The Data by John Alberg and Michael Seckler, Euclidean Technologies

The Setup (Revisited)

In Part 1 of this series we discussed the background and problem setup for how one can apply deep learning to predicting whether a stock will outperform the median performance of all stocks over a one-year period. To make this prediction, we feed the model historical company fundamental and price data. By fundamental data we mean information that can be found in a company’s financial statements. Because we use a recurrent neural network (RNN), on each time step (month) the model can make a prediction using (if needed) all of the historical price and fundamental data...