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, Your work is spectacular, the same as you play ice hockey. :)
I am from China, the logic of chinese stock is some different from the other countries (as you kown ?), but I think your idea is very useful for us.
So, Would you please share the complete code to my email: sun-sea-sky@foxmail.com
I want to learn more from you, thank you!
Hi Boris, Your work is spectacular, the same as you play ice hockey. :) I am from China, the logic of chinese stock is some different from the other countries (as you kown ?), but I think your idea is very useful for us. So, Would you please share the complete code to my email: sun-sea-sky@foxmail.com I want to learn more from you, thank you!