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 hope you are doing well. I am currently second-year student at NYU's financial engineering program. Also, I am currently doing a capstone project about time series generation and your work seemed really interesting and inspirational to me. I would be more than if you can share the code with me. Thank you for your time and help.
Hello Boris,
I hope you are doing well. I am currently second-year student at NYU's financial engineering program. Also, I am currently doing a capstone project about time series generation and your work seemed really interesting and inspirational to me. I would be more than if you can share the code with me. Thank you for your time and help.
Kind regards, Deniz Kural (dk3703@nyu.edu)