In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
I am college student majoring in computer science and applied math and am very interested in the application of deep learning in finance. I have learned related concepts like GAN, LSTM, and VAE and would really like to take a look at your code to get more insights.
Would you please share your code and data with me?
My email address is tzheng2@nd.edu
Hi Boris,
I am college student majoring in computer science and applied math and am very interested in the application of deep learning in finance. I have learned related concepts like GAN, LSTM, and VAE and would really like to take a look at your code to get more insights.
Would you please share your code and data with me? My email address is tzheng2@nd.edu
Thank you so much.
Best, Leo