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.
Hi Boris Banushev,
I'm a student in Fintech and I am very interested in the GAN you described.
I really hope you can share the code and dataset to help me study.
My email is yukaiee@126.com
Thanks! Best regard.