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.
Thank you very much for sharing this! I am a student who is learning GAN for prediction and very interesting in your research,Could you share the code with me. My email is s21020100@s.upc.edu.cn
Hi Boris,
Thank you very much for sharing this! I am a student who is learning GAN for prediction and very interesting in your research,Could you share the code with me. My email is s21020100@s.upc.edu.cn
I would greatly appreciate it.
Sincerely, David