Prediction using Recurrent Neural Network on Time series dataset

Question

Description

Given a dataset that has 10 sequences - a sequence corresponds to a day of stock value recordings - where each constitutes 50 sample recordings of

Answer 1

I hope I this will help you out

The recurrent network structure

---

A few tips

Choosing your recurrent network

The more mature Long Short Time Memory (LSTM) neural network is a great fit for this kind of task. LSTM is able to detect common "shapes" and "variations" in the stock value "graph", and there is A LOT of research which tries to prove that such shapes actually occur in real life! See this link for an example.

Accuracy

If you want the network to achieve higher accuracy, I would recommend you to also feed the network the stock values from the previous year (at the exact same date), so that the number of inputs doubles from 50 to 100. Though the network might be well optimised on your dataset, it will never be able to predict the unpredictable behaviour of the future ;)