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.
I am trying to learn more about GAN as I find it difficult to make good stock predictions with just LSTM. I came across your article and found it very interesting.
nah just slap more hidden layers and call it good, mine fits pretty well and made 40% accurate future prediction which is a pretty alright indicator for algo trading imo
IISuperluminaLII
commented
4 years ago
Hi Boris,
I am trying to learn more about GAN as I find it difficult to make good stock predictions with just LSTM. I came across your article and found it very interesting.
Is it possible to get the code for this project?
Regards. Raphaël