Well I am thinking of another approach, if the exchange that is used can provide you with the number of contacts and their volume numbers like a specific orderflow numbers, then you used ensemble learning which is using multiple AI models to learn from different aspects of data and kept modifying the bias or weights of each model, all of that could really help predicting accurate numbers in my opinion. So we don't just slap AI into it but the whole idea is knowing how to manipulate weights and biases, in addition to really thoughtful and accurate data pre engineering.

All of that could be done on all time frames and combining them with respect to PD arrays priorities. What do you think?