What's the best way to measure 30 day volatility average as a single number return for currency pairs?
Suppose a model train service is configured, the deployment-rig to trade a currency pair runs. Now you want to identify which currencies have the greatest volatility to benefit from trade over.
Background: Python, CNN's Keras, Binance. Looking to identify which pairs have highest 30 day volatility to trade upon.
My initial thoughts is the average (sum/total) of standard deviation of closing price over 30 days. Intuition says there should be a quick trick to get the 30 day volatility over a time interval which is proving a good challenge to source.
Submitted October 17, 2020 at 04:00AM by Dream3r111