# A Cleaner Dashboard: Z-Scores Instead Of Price Changes

Use volatility-aware price changes for more context in your dashboards

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*.