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.
Your article sounds very convincing and inspiring!
I'm trying to dive into GAN to implement my own stocks trading bot, but there is not much information on the Internet on this subject.
I would appreciate the opportunity to view your source code.
Hi Boris,
Your article sounds very convincing and inspiring! I'm trying to dive into GAN to implement my own stocks trading bot, but there is not much information on the Internet on this subject.
I would appreciate the opportunity to view your source code.
My email is felix.weizman@gmail.com
Thank you!