Direct Answer
A custom composite that combines several breadth readings into one score. There is no standard definition: it is commonly an equal-weighted average of normalised measures such as the percent of stocks above a moving average and an advancing volume percentage. Higher scores mean more of the underlying breadth measures are strong at the same time, and falling scores mean breadth is deteriorating.
Risk-On Breadth Composite: Formula, Meaning, Signals, Examples and How to Use It
How Is Risk-On Breadth Composite Calculated?
A custom composite that combines several breadth readings into one score. There is no standard definition: it is commonly an equal-weighted average of normalised measures such as the percent of stocks above a moving average and an advancing volume percentage.
Formula: Composite = (component 1 + component 2 + ... + component n) / n, with each component scaled 0 to 100
Inputs:
- Component breadth measures
- Scaling of each measure to 0-100
- Weights, if not equal
Worked example. If three breadth readings are 62, 55 and 71, their equal-weighted average is 62.7. The inputs are illustrative numbers, not market data.
Reading it. Higher scores mean more of the underlying breadth measures are strong at the same time, and falling scores mean breadth is deteriorating. The composite is most useful for tracking direction and for flagging when many measures agree.
Limits. Because the recipe is not standard, the composite is only as meaningful as its components and weights, and results cannot be compared across providers. Averaging also hides which component is driving the change.
What is Risk-On Breadth Composite?
A custom composite that combines several breadth readings into one score. There is no standard definition: it is commonly an equal-weighted average of normalised measures such as the percent of stocks above a moving average and an advancing volume percentage.
How to use Risk-On Breadth Composite
Higher scores mean more of the underlying breadth measures are strong at the same time, and falling scores mean breadth is deteriorating. The composite is most useful for tracking direction and for flagging when many measures agree. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.
Strengths
- Rescaling each component to 0 to 100 before averaging puts measures with different units on one footing, so the composite value is directly readable.
- Combining several breadth readings means no single misleading input, such as one volume day, carries the whole score.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- Components such as moving-average percentages and volume percentages tend to move together in strong trends, so the average can double count one underlying move.
- The scaling method, whether fixed bounds or a historical percentile, changes the output, and a percentile scale shifts as new data are added.
- Correlated indicators can create false confidence by repeating the same underlying information.
Editorial and risk note
This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance.
Frequently Asked Questions
Is Risk-On Breadth Composite a buy or sell signal?
No. Higher scores mean more of the underlying breadth measures are strong at the same time, and falling scores mean breadth is deteriorating. Because the recipe is not standard, the composite is only as meaningful as its components and weights, and results cannot be compared across providers. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions.
What is the best setting for Risk-On Breadth Composite?
Risk-On Breadth Composite is computed from component breadth measures; scaling of each measure to 0-100; weights, if not equal, so the choices that matter are the data convention and the window it is read over. Test those across instruments, regimes and out-of-sample periods instead of fitting one historical winner.
Can Risk-On Breadth Composite be used by itself?
Because the recipe is not standard, the composite is only as meaningful as its components and weights, and results cannot be compared across providers. Averaging also hides which component is driving the change. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Risk-On Breadth Composite work on every timeframe?
The calculation (Composite = (component 1 + component 2 + ... + component n) / n, with each component scaled 0 to 100) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it.
Why does Risk-On Breadth Composite give false signals?
Components such as moving-average percentages and volume percentages tend to move together in strong trends, so the average can double count one underlying move. The scaling method, whether fixed bounds or a historical percentile, changes the output, and a percentile scale shifts as new data are added. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Risk-On Breadth Composite be backtested?
Rebuild Risk-On Breadth Composite from component breadth measures using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline.