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Does a 0–100 swing setup score predict which stocks rise over the next 10 sessions?

Swing Setup Score (M-014). Short answer: the hub rates it NOT RELIABLE.

Data as of .

The verdict

NOT RELIABLE as a screening or ranking input: the composite sign-flips out-of-sample and was already removed from M-011 for that reason on 2026-08-15; the tab's own display as descriptive context is the appropriate remaining use.

Development summary: The 2026-07 re-weight replaced flat momentum components with vol-expansion + pullback depth + long-term RS on a modest in-sample decile signal (56.9% vs 51.8% up-rate) that then sign-flipped OOS; dropped from M-011 scoring 2026-08-15.

What the review allows

  • As descriptive, per-symbol component context (which of RS/vol-expansion/pullback is elevated) on the Swing tab only.

What the review rules out

  • Use the Setup Score or its deciles to screen, rank, or size positions — it sign-flips out-of-sample and was removed from M-011 for exactly this reason.
  • Assume the in-sample decile separation (56.9% vs 51.8%) generalizes forward.

What it predicts

ItemDetail
Question it answersWhich names are most entry-ready right now, combining relative strength, trend quality, volume accumulation, base tightness and pullback depth into one 0-100 score?
MethodWeighted composite score
How it worksWeighted composite (empirically re-weighted, not equal-weighted); decile-conditioned forward-10-session base rates backtested over a 4-year multi-market grid
InputsBollinger-width expansion (50%), Pullback depth in ATRs (30%), 6-month relative strength (20%)
Output0-100 Setup Score per symbol, plus decile-level forward R/up-rate/expected-move context
Horizon10 sessions (the window the decile base rates are measured over)
Coverage~1,200-1,700-name panel (S&P 500 + Nifty + curated watchlists)
MarketsUS, India
Model typeModel · ML/Stat
StageRetired to heuristic
Versionv1, first recorded 3 Sep 2026

Validation evidence

Training data: not stated. Test data: not stated. Out-of-sample design: none.

Headline results from the model's development record, as the hub publishes them.
MeasureResultCompared withNote
Decile 10 vs 1 up-rate56.9%51.8% (decile 1)~1,200-name multi-market grid x 1000 days, re-weight test
Decile 10 vs 1 median 10d return+1.03%+0.25% (decile 1)same grid
Rejected componentsRS 1/3m, trend efficiency, volume accumulation, tight basestested FLAT over fwd-10-session outcomesclassic momentum inputs, not kept
Out-of-sample behavioursign-flipsin-sample decile monotonicityled to removal from M-011's scoring, 2026-08-15
The hub's standard metrics for this model class (only those the record measured).
MetricSample / windowCompared withValueRange (CI)
Precision at k (headline)in-sample · top decile up-ratedecile 1 51.8%56.90%n/a

What the validation review found

Is the design sound? The underlying instinct (measure which components predict, don't assume) is sound; the failure is that the measurement itself did not generalize out-of-sample, which the owner correctly acted on by downgrading it.

Backtest. In-sample only in the reviewed evidence; the out-of-sample sign-flip is recorded as a fact (and acted on) but its own test design is not in the material reviewed here.

Limitations

Questions

Is the Swing Setup Score validated?
Its validation review dated 3 Sep 2026 rated it NOT RELIABLE as a screening or ranking input: the composite sign-flips out-of-sample and was already removed from M-011 for that reason on 2026-08-15; the tab's own display as descriptive context is the appropriate remaining use.
What does the Swing Setup Score predict?
It answers: Which names are most entry-ready right now, combining relative strength, trend quality, volume accumulation, base tightness and pullback depth into one 0-100 score? Output: 0-100 Setup Score per symbol, plus decile-level forward R/up-rate/expected-move context. Horizon: 10 sessions (the window the decile base rates are measured over). Coverage: ~1,200-1,700-name panel (S&P 500 + Nifty + curated watchlists).
How was the Swing Setup Score tested?
Training data not stated, test data not stated, out-of-sample design: none. Decile 10 vs 1 up-rate (in-sample re-weight test): 56.9% vs 51.8%; Decile 10 vs 1 median 10d return: +1.03% vs +0.25%; Out-of-sample stability: sign-flips — dropped from M-011 scoring 2026-08-15.

Source: the Model Hub's public model register, as of 6 Nov 2026. The M-014 page in the live Model Hub carries the full development and validation record, monitoring and open decisions. All 30 models and their verdicts.

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