Developing an EA that depends on higher than average volatility in well directed markets for Edge.
So far it avoids high volatility created by economic news releases and super high volatility from rare events like Brexit etc...
But would like to model/predict the likely max spread for a future time interval that encompasses 85% of my trade open times, with normalized current volatility and volumes.
Pulled the tick data as CSV files. But there will be a little bit of a problem arranging the tick data into a min by min time series to work out the vols and volumes in each range. I'm told it's easily done on Python or R and would like to know if anyone has any suggestions to speed up or make the modelling process more time intelligent and efficient/ has experience doing this or something similar.