Chart & Technical · ADI

Strategy Cup Tier for ADI

AI-generated plain-English read of strategy cup tier for ADI. Updated daily.

Strong tier — no statistical validation

low

Cup-3 performance (an unknown margin) without MC validation. The outperformance is real on the val window but statistically indistinguishable from a lucky run — proceed with caution.

What will probably happen

  • High cup tier without MC significance: in-sample results look good but the forward edge is unconfirmed — reduce size and watch the next val window closely.
  • Walk-forward stability is low — the edge broke down on rolling out-of-sample periods. Parameters that looked good in-sample may not generalise.
  • 10-29 trades — the sample is thin. Percentile statistics are noisy and overfit risk is elevated.

What to do

If you HOLD this stock and follow this strategy
Strong tier but incomplete validation — hold with reduced position size. Set a drawdown trigger to re-evaluate if performance decays.
If you're EVALUATING whether to use this strategy
Strong tier without validation — paper-trade. Strong cup without MC significance often reflects lucky optimisation on the training window.
If you trade OPTIONS on this strategy's signals
Don't increase options size on this strategy's signals — the edge may not persist out-of-sample. Treat signals as weak directional hints only.

Weak credibility profile — no MC significance or DSR support; walk-forward stability is low.

Technical details

Technical analysis

Cup tier
cup_3 (strong)
Robustness
Fragile
Tier grade
Strong
Trade count
12
MC significant
No
Sample quality
Small Sample
Validation window
—
Statistical support
No Validation
Deflated Sharpe Ratio (DSR)
0.003
Delta return vs buy-and-hold
—
Walk-forward stability score
0.00

Key levels

Key price and metric levels
LevelValue
dsr0.003
cup tier3
num trades12
robustness score0

Caveats

  • Cup tiers reflect val-window performance. Live forward returns may differ from backtest — even validated strategies have drawdown risk.
  • High cup tier without MC significance is a classic overfit warning sign. The in-sample optimiser can find parameter sets that look exceptional on the training window without generalisable edge.

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