these recommendations were three of the stocks with the best predicted outcomes from our model. our model is based on monthly trends in the stock market and in companies' performance.
we used machine learning algorithms on the most recent real-time stock data, testing models ranging from complex recurrent neural networks and SVRs to basic linear regression. ultimately, we optimized exponential moving averages to use multiple-length windows concurrently, drawing insights on whether the stock will perform better or worse in the next time step based on their crossover ratio.