Sierra Chart footprint imbalance settings: how ratio, thresholds and data aggregation change highlighted cells

What Sierra Chart footprint imbalance settings actually control

Sierra Chart footprint imbalance settings decide which cells in a Numbers Bars footprint get highlighted. A cell is highlighted when one side's volume beats the compared side by your chosen imbalance ratio and also clears any minimum volume filter you set. The same market can look very different depending on how you aggregate the data feeding those comparisons. That includes row size, bar period and the granularity of your stored data.

This article focuses on that relationship. It covers how the inputs interact, why highlights appear or disappear when you change aggregation, and what to check so the colors on your chart mean what you think they mean. If you need the full diagonal configuration walkthrough, see the guide to Sierra Chart diagonal imbalance settings. This article stays on the logic behind the highlighting.

The three inputs that decide a highlight

Footprints in Sierra Chart are built with the Numbers Bars study, not the Market Depth settings. Open it with Analysis >> Studies, select Numbers Bars in the chart's study list, then click Settings. Input names can change between versions, so read them in your own installation and confirm their meaning against the Numbers Bars documentation. Conceptually, three things work together.

Comparison method: diagonal or horizontal

A horizontal comparison checks bid volume against ask volume on the same price row. A diagonal imbalance compares ask volume at one price with bid volume one row below. In other words, it compares buyers lifting the offer with sellers hitting the bid one level lower. Most order flow traders use diagonal because that is how a market actually trades through levels. Whichever method you choose, every highlight on the chart depends on it, so confirm which one is active before you interpret anything.

Imbalance ratio

The imbalance ratio is the multiple one side must exceed. A 3:1 ratio means the dominant side needs at least three times the compared volume. Some inputs express this as a percentage, where 300 percent corresponds to 3:1. Check whether your input expects a ratio or a percentage. Typing 3 into a percentage field gives you a nearly meaningless threshold.

Lower ratios, such as 1.5:1, highlight a large share of cells and turn the footprint into noise. Higher ratios, such as 4:1, highlight far fewer cells. They can miss gradual shifts in aggression.

Minimum volume filter

Without a volume floor, tiny numbers create absurd ratios. A row with 1 contract on the bid and 4 on the ask is technically a 4:1 imbalance, but it says very little about the market. A minimum volume filter tells the study to ignore comparisons where the dominant side, or both sides depending on the input, is below a set size. Check the documentation to see which side your version applies the filter to.

A worked ES example: same trades, different highlights

Take an ES footprint with one tick per row. ES moves in 0.25 increments. Settings are a diagonal comparison, a 3:1 ratio and a 10 contract minimum.

• Ask at 5000.25: 72 contracts. Bid at 5000.00: 20 contracts. The ratio is 3.6:1 and both sides clear the minimum, so the ask cell at 5000.25 is highlighted.
• Ask at 5000.50: 30 contracts. Bid at 5000.25: 14 contracts. The ratio is about 2.1:1, so there is no highlight.
• Ask at 5000.75: 9 contracts. Bid at 5000.50: 2 contracts. The ratio is 4.5:1, but the dominant side is under 10 contracts, so the filter suppresses it.

Now aggregate the rows to four ticks, one full point per row. Rows 5000.00 to 5000.75 merge into one row, and their bid and ask totals add up. The single strong diagonal at 5000.25 is now diluted inside a larger row and compared against a different neighboring row. It can lose its highlight entirely. The reverse also happens. Several modest one tick rows can sum into a combined row that crosses the ratio.

Nothing about the trades changed. Only the aggregation did. So a highlight is a property of your settings plus your data, not an objective fact about the market.

Why data aggregation matters as much as the ratio

Row size per instrument

Row size is the price range each footprint row covers. It may be set in the Numbers Bars inputs or follow the chart's tick size, depending on your version and setup. Check both the study inputs and Chart Settings. Typical considerations:

• ES (0.25 tick): one tick rows are common because volume per level is usually deep enough for ratios to mean something.
• NQ (0.25 tick): price moves through many more ticks per bar, so per row volume is thinner. Some traders widen rows so imbalances are not driven by small prints.
• CL (0.01 tick): one cent rows spread volume very thin. Aggregating several ticks per row usually gives more stable comparisons. Your minimum volume filter then needs to be rethought, because each row now holds more contracts.
• EURUSD: spot forex has no centralized exchange volume, so a spot feed may not provide true bid and ask traded volume. For footprint work, the CME Euro FX futures contract is the usual exchange-traded reference. Check what your data feed delivers before trusting any imbalance colors.

When you change row size, revisit the minimum volume filter at the same time. A 10 contract floor that suits one tick ES rows becomes almost no filter at four tick rows.

Bar period

A 1 minute bar and a 5 minute bar contain different amounts of volume per row. Longer bars accumulate more contracts, so more rows clear the minimum volume, and ratios can smooth out as both sides grow. Range or volume based bars change this again. If you compare footprints across charts, keep the bar type and period identical, or you are comparing two different filters.

Data granularity

Imbalance calculations need correct bid and ask volume at each price, which requires tick by tick data. In Global Settings >> Data/Trade Service Settings, Intraday Data Storage Time Unit should be set to 1 tick. With coarser storage, historical bars can lose the bid and ask split. Cells may then show zero on one side, which produces false imbalances or none at all. The tick by tick data configuration documentation explains the requirement. For a full verification routine on historical cells, see Sierra Chart footprint tick data requirements.

Numbers Bars highlighting: making the colors readable

Numbers Bars highlighting is the visual output of all the logic above. Keep it simple:

• Use one color for ask-side imbalances and one for bid-side imbalances. Keep both distinct from the colors you use for delta or the point of control.
• If your version offers stacked imbalance marking, which flags several consecutive imbalanced rows, treat it as a separate layer. Enable it only after the single cell highlights look sensible.
• Avoid highlighting the cell background and the text at the same time unless you have tested readability at your normal zoom level.

If you want to understand the other numbers in each cell, such as bar delta and volume statistics, read Sierra Chart Numbers Bars calculated values explained.

Building and testing these combinations takes time. A Sierra Chart footprint chartbook that already has Numbers Bars, bid ask volume, delta and imbalance highlighting configured gives you a working baseline. You can then adjust ratio and row size from there.

A short checklist after changing settings

1. Confirm whether the comparison method is diagonal or horizontal.
2. Confirm whether the ratio input is a multiple or a percentage.
3. Pick a few highlighted cells and compute the ratio by hand to verify the study is doing what you expect.
4. Check one suppressed cell to confirm the minimum volume filter is working.
5. Change row size by one step and note how many highlights appear or vanish. That shows how sensitive your setup is to aggregation.
6. Scroll back through history and look for rows with zero on one side, a sign of missing tick data.

Conclusion

Imbalance highlights in Sierra Chart are the product of three choices: comparison method, ratio and minimum volume. Row size, bar period and data granularity sit on top of those choices. Change any one of them and the highlighted cells change, even though the underlying trades do not. Treat your imbalance settings as a measuring tool that you calibrate per instrument. Verify a few cells by hand after each change, and keep aggregation consistent across the charts you compare. None of this produces trading signals on its own. It only makes the chart an accurate picture of what was traded.

If you prefer to start from a tested layout, browse the Sierra Chart chartbooks at SierraOnShop.

FAQ

Should I use the same imbalance ratio on ES and CL?

Not necessarily. Volume per row differs a lot between instruments and row sizes, so a ratio and minimum volume that filter well on ES may over-highlight or under-highlight CL. Calibrate each instrument separately and save the settings per chart.

Why do my imbalance highlights change after reloading the chart?

A reload recalculates from stored data. If live data was captured at tick level but older data was stored more coarsely, or a backfill filled gaps differently, the bid and ask totals can change and so can the highlights. Check your Intraday Data Storage Time Unit and run a data verification.

Can I save my imbalance settings and reuse them on other charts?

Yes. You can save the Numbers Bars study with your settings in a study collection, which uses the .stdycllct extension, or save the whole chartbook as a .Cht file. See the Sierra Chart study collections documentation for how collections are stored and applied.

Do imbalances work on tick, volume or range bars?

The comparison logic applies to any bar type that Numbers Bars supports. The volume each bar contains depends on the bar type, though, so ratios and minimum volume filters behave differently. Keep bar type fixed when comparing footprints.