So I have a large ~1 GB CSV file with forex tick price data for a whole year, formatted like below:
My question is, how can I wrangle with this data in the following ways:
- Cut out 10000 randomized 30 minutes sections of the data.
- For every 30 minutes section, make simulated Long AND Short trades at the 6 minute mark, with a certain predetermined stop loss and take profit. Then label each piece of 30 minute section into one of 4 categories: Should go long, Should go short, Both are profitable (unlikely, but let’s list it out anyway), and Either is okay.
- Generate timeseries data of the first 5 minute of every 30 minute section in a format that an LSTM neural network in DLS can process, with correct labeling and everything.