For the Geeks

For the Geeks

This page is optional reading. You do not need to understand these mechanics to use Axiom DC Pro effectively. But if you are the kind of person who trusts a tool more when you understand how it works — and you want to verify its behavior with a calculator rather than taking the output on faith — this page is for you.

Two things are explained here: how the blended channel computes its values, and how cross-ticker scaling maps one instrument's Donchian structure into another instrument's price space.

How the blended channel works

The short version

The blend computes a normalized weighted average. For each of the three channel components — upper, basis, and lower — it takes every enabled slot with a non-zero weight, multiplies that slot's value by its weight, sums those products, and divides by the total weight. Upper, basis, and lower are blended independently. There is no interaction between the three components during the blend calculation.

One important qualifier: the "blend sits between the contributing channels" intuition only holds when the weights are non-negative and the total contributing weight stays positive. The script does not clamp weights to positive-only values.

The walkthrough

Suppose you have two slots enabled:

Blended upper:

(4520 * 60 + 4550 * 40) / (60 + 40) = (271200 + 182000) / 100 = 453200 / 100 = 4532

Blended basis:

(4510 * 60 + 4525 * 40) / (60 + 40) = (270600 + 181000) / 100 = 451600 / 100 = 4516

Blended lower:

(4500 * 60 + 4500 * 40) / (60 + 40) = (270000 + 180000) / 100 = 450000 / 100 = 4500

In this example, the blended upper is 4532, which sits between the two slots' upper values (4520 and 4550), closer to DC 01 because DC 01 has the higher weight. The blended basis is 4516, again closer to DC 01's basis. The lowers happen to be the same, so the blend is 4500 regardless of weight.

What happens at the boundaries

Weight = 0: The slot is excluded from the blend. Its values are not included in the sum and its weight is not included in the denominator. Setting weight to 0 is the correct way to keep a slot on the chart without it influencing the composite.

Only one slot with weight > 0: The blend converges to that single slot's values. The blended channel becomes a thicker copy of one slot. There is no aggregation happening.

No positive total weight: If every contributing slot is disabled, at weight 0, or the weight mix sums to 0 or below because of negative values, the blend has nothing usable to compute. In that case the function falls back to zeroed blend values.

What this tells you about trust

The blend does not add information. It synthesizes information from the slots you configured, and the synthesis is only as meaningful as the inputs and weights behind it.

There are two failure modes worth understanding:

The blend looks authoritative but is dominated by one slot. If DC 01 has weight 80 and DC 02 has weight 20, the blended upper will sit within 20% of DC 01's upper. The blend is not adding much — it is mostly repeating DC 01 with a small pull from DC 02. You are looking at one slot wearing a composite label. Before trusting the blend to represent multi-timeframe consensus, check whether the weights actually distribute influence across diverse timeframes.

The blend looks calm but hides disagreement. When one slot reads bullish (price above basis) and another reads bearish (price below basis), the blend produces a value in between. That middle value can look like neutral structure. It is not. It is two opposing structural reads averaged into a single number that masks the tension. The individual slots are more honest about what is happening than the blend is in this situation.

You can verify the blend at any time by reading two slots' values from the data window, plugging them into the formula above, and comparing to the blended values. If the numbers match (they should, to rounding), you know exactly what the blend is doing. If they do not match, check for a third contributing slot, a hidden slot with weight, or a weight configuration you forgot you changed. The act of doing this calculation once, with real numbers from your chart, will give you a better feel for what the blend actually represents than any amount of reading about it.

How cross-ticker scaling works

The problem it solves

When a slot uses an alternate ticker (say, SPY on an ES chart), the alternate instrument's Donchian Channel values are in a different price space. SPY might be trading at 450 while ES is at 4500. If you plotted SPY's raw Donchian Channel on the ES chart, the lines would be invisible — they would sit at the bottom of the chart, far below ES price.

The scaling brings the alternate instrument's channel into the chart instrument's price neighborhood so the structural information is visible and spatially meaningful.

How it scales

The indicator computes a ratio between the chart instrument's higher-timeframe close and the alternate instrument's higher-timeframe close. Both closes come from the same HTF context — the same timeframe, the same On Bar Close behavior.

ratio = chart instrument's HTF close / alternate instrument's HTF close

The alternate instrument's raw Donchian values (upper, basis, lower) are then multiplied by this ratio:

scaled upper = raw upper * ratioscaled basis = raw basis * ratioscaled lower = raw lower * ratio

A concrete example

Chart instrument: ES, current HTF close = 4500 Alternate instrument: SPY, current HTF close = 450

ratio = 4500 / 450 = 10.0

If SPY's raw Donchian upper is 455, the scaled upper on the ES chart is:

455 * 10.0 = 4550

This puts SPY's structural ceiling at 4550 on the ES chart, which is in the right neighborhood to compare against ES's own structural levels.

Why the ratio drifts

The ratio is recalculated every bar using the current closes. If ES moves from 4500 to 4600 while SPY moves from 450 to 455, the ratio changes:

Old ratio: 4500 / 450 = 10.0New ratio: 4600 / 455 ≈ 10.11

This shift means the scaled channel values change not just because SPY's structure changed, but because the ratio between the two instruments changed. Over time, if the instruments trend in different directions or at different rates, the ratio drifts further. The scaled channel slides relative to the chart's price in ways that reflect the relationship between the instruments, not just the alternate instrument's structure.

When the drift matters

When the instruments trend together: The ratio stays relatively stable. The scaled channel tracks the alternate instrument's structural behavior faithfully. This is the case where cross-ticker scaling works well — correlated instruments like ES and SPY, gold and silver, or instruments that share a common driver.

When the instruments diverge: The ratio moves, and the scaled channel starts to reflect the divergence rather than just the alternate instrument's structure. The channel may drift to levels that do not correspond to any meaningful structural position on either instrument. At this point, the scaled channel is still mathematically correct — the scaling formula is doing what it does — but the structural information it carries has degraded.

How to verify

1. Open the chart instrument on one tab and the alternate instrument on another.

2. On the alternate instrument's chart, add a standard single-timeframe Donchian Channel with the same length and timeframe.

3. Read the alternate instrument's raw upper, basis, and lower from the data window.

4. Read both instruments' most recent closes.

5. Compute the ratio (chart close / alternate close).

6. Multiply the alternate instrument's raw values by the ratio.

7. Compare to the cross-ticker slot's values on your main chart. They should match closely.

If they match, the scaling is doing exactly what it should. If they do not match, check whether both charts are on the same timeframe and whether On Bar Close settings agree.

What this is not

Cross-ticker scaling is not normalization. Normalization in the statistical sense involves standardizing values relative to distributions, volatility, correlation, or other statistical properties. This scaling does none of that. It is a proportional remapping — a ratio multiplication that puts the alternate instrument's values into the right price neighborhood on the chart.

This distinction matters in practice because the scaling does not account for differences in volatility, beta, or correlation structure between the two instruments. If SPY's volatility doubles relative to ES during a market event, the scaled channel's width does not adjust — it still uses the simple close-ratio. The channel will be wider or narrower than it "should" be if you were thinking in normalized terms, and that discrepancy is invisible on the chart. The scaled channel just looks like a channel.

The honest way to think about cross-ticker scaling: it puts another instrument's structural picture into your chart's price neighborhood so you can see it. The neighborhood is right. The specific house numbers — the exact levels of the scaled upper, basis, and lower — are approximate and drift with the ratio. Use it for structural direction (is SPY's structure confirming or contradicting ES?) rather than structural levels (did price just touch the scaled SPY upper at exactly this price?). The former is what the approximation supports. The latter asks more precision than it can deliver.