Let's say we have an OHLCV dataset for a universe of stocks. We want to create features based on these price data. Since each stock may have a very different price range from the other if we just take log-delta (eg. open-close) a stock that has a price range around 1000-2000 would look very different from another that has a price range of around 1-10. This will happen also for stock (or any instrument) that has a drastic shift in prices over time. For instance, BTC recent steep rise in value.
What would be a good way to standardize or normalize these features across different stocks of various price ranges?