Macro Net Score and Confidence Explained
Learn how to read Net Score, confidence, and mixed macro backdrops without turning the result into a trade signal.
What Net Score is trying to summarize
Net Score is the Macro Model's compact summary of the current macro backdrop. It helps users understand whether the feature mix leans more pressure-heavy or more constructive. It is not a trade signal. It is a context score that should be interpreted with the scenario distribution and the payoff table.
A positive Net Score can appear when the macro feature mix is broadly supportive. A negative Net Score can appear when policy, inflation, curve, sentiment, or credit conditions look more stressed. A near-zero or mixed reading means the environment may contain both supportive and pressure-heavy inputs.
What model confidence means
Confidence describes the quality and consistency of the macro read. A cleaner feature mix can support a higher-confidence interpretation. A mixed feature mix can lower confidence because the inputs are not pointing in the same direction.
For example, inflation pressure may be improving while credit conditions remain uneven. Sentiment may recover while the policy backdrop remains restrictive. Those mixed cases can produce useful information, but they should be read with more caution than a clean, aligned macro setup.
How to read mixed macro conditions
Mixed conditions are common. Markets often move through transitions where one macro input improves before another. The Macro Model is designed to show that complexity without requiring users to inspect every raw indicator manually. A mixed confidence read tells users not to rely on a single headline number.
Where confidence fits in the workflow
Confidence should be compared with the other TSL model outputs. If macro looks constructive but trend quality is weak and risk stress is elevated, the overall research picture is not as clean. If macro, trend, timing, persistence, and risk are aligned, the read is more internally coherent.
FAQ
Is high confidence the same as a positive result?
No. Confidence describes the clarity of the macro read, not whether the read is bullish or bearish.
Can a negative macro read have high confidence?
Yes. If several macro features point toward pressure, the model can have a clearer negative-context read.
Should low confidence be ignored?
No. Low or mixed confidence is useful because it tells users to inspect the scenario table and compare with the other models.