The stock market has always been a core interest in predictive analytics. Thus it came as no surprise when one of our clients seek our assistance in his investment strategy.

We designed an intelligent asset allocation system consisting of a Long Short-term Memory Recurrent Neural Network (LSTM), which predicted the expected return for every asset in a portfolio. In order to estimate an asset’s risk, a novel technique called Variational Dropout was used. Another neural network was used to determine the optimal set of weights for the portfolio’s assets.

These combined algorithms provided an investment strategy with returns comparable to Wealthfront.