QuoteOriginally posted by: outrunI would advice to forget about the NN and use the much better mathematically founded Support Vector Machines. Also: instead of a target vector, it might be better to use reinforcement learning because that focuses on maximizing on overall reward without explicitly knowing the reward of all little steps in between. Another option is to condition the objective (of finding the best action) onto your current position. Instead of finding the best action at some point in time, find three best actions, one in case you are short, one when long and one when having no position. This makes ik suitable for Bellman-ish dynamic programming in a second phase. Your best action might also differ based on your current position due to transaction cost and risk/return optimization.Thanks foryour nice suggestions. Generally are we able to improve the prediction accuracy on test data by using SVM? If yes, up to what percentage of accuracy we can predict signals correctly.