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,
Just found your research and think that this is a great research you've made. I am very inspired by it.
Can I can get your GAN and DRL source code please, so I can study it further ?
My email is: endro.koesno@gmail.com
Thanks a lot.