Goal : Using deep learning to build a ML model which would predict the right places where a stock price will increase, decrease or stay stable.
For the current question, assume the labels are well defined.
As features I used the limit order book, but I did not get a lot of success. So I realised that I didn't have all the features to accomplish my goal. In reading the following paper [login to view URL] on page 8, I didn't consider the market and cancellation orders. A setback I got is I did not find a vendor to provide the market orders separately from the limit orders. So in the moment I have the full market depth from algoseek. You can find a sample here [login to view URL]
Subtask 1 : Extract the market orders from the full market depth/tick data.
Subtask 2 : I need to feed a NN model with limit, market and cancellation orders. You role is to reformat the full market depth/tick data so that I can get the limit, market and cancellation orders with a 1 second timestamp.