Most investors or traders’ dashboards includes a watchlist with the field “percentage price change”. Perhaps you have several fields for this. Daily, weekly, monthly.
Here’s a useful way to filter out the noise and get a nicer view of the market action:
Re-scale all the moves in terms of standard deviations
My preference, although it relies on having options data, is to use implied volatility which is the market’s consensus for what the standard deviation is.
Here’s the formulas:
- Daily = % change on day * 16/IV from yesterday’s ATM straddle
- Weekly = % change on week * 7.2 / IV week ago
- Monthly =% change on month * 3.5 / IV month ago
Implied vols are annualized numbers so the factors (16, 7.2, and 3.5) re-scale the vols for the measurement period.
These are just Z-scores!
Observations
- If the absolute value of any of these numbers exceeds 1, the asset moved more than 1 implied standard deviation.
- You can put all the assets on the x-axis of a barchart to see them visually. If you want, you can even subtract 1 from each value to see the excess move above one standard deviation. Or you set your filter at any other level.
- This is not a tool to find opportunities or anything fancy, it’s literally just a cleaner way to visualize price moves and ignore noise.
I was too lazy to make one for stocks or futures, but the output will look like this (instead of MPG imagine it was “price change”):
If you want to use straddle prices which represent mean absolute deviation or MAD then divide the formulas further by .8.
The reason you use .8 is explained in my post Straddles, Volatility, and Win Rates.
If you use options to hedge or invest, check out the moontower.ai option trading analytics platform