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 project is super enlightening for me. I am Qichang Zheng, a senior student at XJTLU. I have been working on my Final Year Project to develop a hybrid model for stock prediction like yours. Therefore I was wondering whether you could bother sharing your source code to me so that I could look into and learn from it.
My Email: qichang.zheng18@student.xjtlu.edu.cn
Hi Boris,
Your project is super enlightening for me. I am Qichang Zheng, a senior student at XJTLU. I have been working on my Final Year Project to develop a hybrid model for stock prediction like yours. Therefore I was wondering whether you could bother sharing your source code to me so that I could look into and learn from it. My Email: qichang.zheng18@student.xjtlu.edu.cn
Thank you very much!
With kindest regards, Qichang