ADI — Analog Devices, Inc.

Report date: 2026-05-26  |  Sector: Technology  |  Last price: $397.07  |  Horizon: 30d  |  Generated: 2026-05-26T07:31:25.499196Z

Forecast summary

Ensemble point +0.19%
80% CI [-8.52%, +9.97%]
95% CI [-12.66%, +15.56%]
Method dispersion 0.0034
Beats RW baseline NO
MC drift (annual) 6.36%
MC sigma (annual) 40.14%
MC paths 1000
Bull target (90th pct) +18.73% -> $471.42
Base target (50th) -0.12% -> $396.61
Bear target (10th pct) -16.45% -> $331.76
Macro regime risk_on_growth
10y yield 4.56%
3m yield 3.59%
Yield-curve slope +0.97%
VIX level 16.59
VIX z-score (252d) -0.48
Sector ETF XLK
Sector relative (90d) +8.85%

Forecast plot (interactive)

Realised volatility

Yang-Zhang annualized (60d) 40.14%
Close-to-close annualized (60d) 37.33%

Per-method comparison

MethodWeightPoint80% lo80% hi95% lo95% hi
linear 25.0% +0.76% -2.92% +4.42% -4.50% +6.43%
monte_carlo 25.0% -0.12% -16.45% +18.73% -24.25% +29.42%
ar1 25.0% +0.11% -2.26% +2.54% -3.49% +3.85%
random_walk 25.0% +0.00% -12.44% +14.21% -18.39% +22.53%

Factor contributions (interactive waterfall)

Factor contribution table

FactorLoadingTicker valueContribution
value_score +0.0495 -2.4784 -0.1226
quality_score +0.0192 -0.5361 -0.0103
momentum_score +0.0286 +2.6739 +0.0765
lowvol_score +0.0173 -0.3666 -0.0063
revisions_score +0.0236 +3.0000 +0.0709
news_activity_score +0.0402 +0.0000 +0.0000
(intercept) - - -0.0005

Factor decay over horizon

Factor IC over time

Per-factor IC backtest summary

FactorMean ICICIR% positiveCumulative attributionn periods
value_score +0.2563 +2.690 100.0% +0.5383 252
quality_score +0.1105 +1.096 86.5% +0.2401 252
momentum_score +0.1428 +1.354 92.5% +0.2460 252
lowvol_score +0.0878 +0.887 82.1% +0.1870 252
revisions_score +0.1375 +1.319 88.9% +0.2738 252
news_activity_score +0.3540 +3.832 100.0% +1.0893 252

Snapshot — fundamentals + technical

Market cap $193.41B
P/E (trailing) 59.2
P/B 5.7
Forward P/E 27.0
PEG 0.91
Dividend yield 111.00%
Beta 1.19
52w high / low $435.72 / $210.80
Distance from 52w high -8.87%
Cross-sectional rank 59 / 92 below median
Panel source (trained model: 2026-05-26 (0d old), universe_size=92, lookback_days=252)
RSI(14) 50.9
SMA50 / SMA200 $365.01 / $293.71
ATR(14) $13.98
Avg volume (20d) 4.16M
Profit margin 26.01%
ROE 9.64%
Revenue growth (YoY) +37.20%
Earnings growth (YoY) +110.50%
Debt/Equity 25.8
Current ratio 1.75
Short ratio 3.32

Forecast accuracy — walk-forward backtest (60d lookback)

Horizonn predictionsDirectional accuracyMAE (return)RMSE80% CI hit ratePearson(pred, real)
1d 691 53.3% 1.53% 2.23% 80.5% -0.012
30d 662 45.9% 10.54% 13.54% 72.8% -0.204
60d 632 55.2% 15.07% 19.92% 70.7% -0.132

Volume momentum (Granville / CGW / Quong-Soudack)

Composite z +0.630
Active signals 7 of 7
MFI(14) 43.84
CMF(20) +0.1481
OBV z (252d) +1.169
VPT z (252d) +1.537
VW-momentum z -0.933
Volume z (60d) +1.546
Relative volume (vs 20d ADV) 1.47x
CMF z (252d) +0.800

Sector rotation & AI-spillover (v6)

Sector ETF XLK
Rel-return 5d / 20d / 60d -7.33% / -12.48% / -13.06%
Sector mom-z 1m / 3m / 6m +2.27 / +2.72 / +1.64
Rotation phase cyclical
AI-factor beta (60d) +0.094
AI spillover score +0.0087
Risk-off corr regime (60d) 0.33 (>0.6 = risk-off; <0.35 = stock-picking)
Sector breadth (% > SMA50) -
Sector dispersion 20d -

Peer comparison (sector-relative valuation & momentum)

Peer signal
MIXED
score -0.39 (9 peers)
P/E percentile
50% (50% cheaper than this)
20d momentum percentile
11% (11% lag this)
Market-cap percentile
56%
Peer set (mcap band 0.2x-5x, same sector)
ANET DELL STX SAP PANW MRVL SNDK CRWD GLW
9 peers in Technology (mcap band 0.2x-5x); signal=mixed; score=-0.39
Decision input: cheap_leader → nudge bias one bucket toward LONG; expensive_laggard → nudge toward SHORT; cheap_laggard = value-trap (neutralize); expensive_leader = crowding risk (neutralize). Folded into Claude critique and one-line PM summary.

Multi-timeframe technical analysis (1wk / 1d / 1h)

Per-timeframe verdict (TradingView-style aggregate of 17 indicators: RSI, MACD, BBands, ADX, Stoch, %R, OBV, MFI, CMF, ATR, SMA50/200, EMA9/21, Donchian, price-vs-SMA200). Counts = how many indicators fired BUY / SELL / NEUTRAL; net strength is the weight-sum delta. Crosses (golden/death, MACD signal cross, Donchian breakout) and the SMA200 trend filter carry 1.5x weight.
1wk verdict
NEUTRAL
4 buy / 2 sell / 11 neutral · net +5.0
1d verdict
NEUTRAL
2 buy / 2 sell / 13 neutral · net +3.0
1h verdict
NEUTRAL
3 buy / 3 sell / 11 neutral · net -1.5

1wk NEUTRAL 4/2/11

RSI(14) 69.2
MACD hist +6.0844
Bollinger %b 0.82
ADX(14) 35.8 RISING
ATR % 6.31%
MFI(14) / CMF(20) 66.4 / +0.156
Donchian pos / break 0.76
vs SMA200 ABOVE
n_bars521

1d NEUTRAL 2/2/13

RSI(14) 50.9
MACD hist -5.5068
Bollinger %b 0.33 SQUEEZE
ADX(14) 32.1
ATR % 3.52%
MFI(14) / CMF(20) 43.8 / +0.148
Donchian pos / break 0.29
vs SMA200 ABOVE
n_bars1253

1h NEUTRAL 3/3/11

RSI(14) 48.8
MACD hist +2.0821
Bollinger %b 0.76
ADX(14) 18.2
ATR % 1.27%
MFI(14) / CMF(20) 50.9 / -0.055
Donchian pos / break 0.81
vs SMA200 ABOVE
n_bars1729

Cross-timeframe confluence

Confluence LONG (0-1) 0.00
Confluence SHORT (0-1) 0.00
Patterns are intentionally selective (Elder triple-screen, daily/hourly divergence, BB-squeeze+breakout, SMA-alignment, MACD/OBV). Most tickers fire 0-2 patterns on any given day. Below: each pattern with its current state (✓ firing / ✗ not firing).
Long patterns
✗ elder_triple
✗ daily_oversold_hourly_bull
✗ bb_squeeze_break_up
✗ sma_align_long
✗ macd_cross_obv
Short patterns
✗ elder_triple
✗ daily_overbought_hourly_div
✗ bb_squeeze_break_dn
✗ sma_align_short
✗ macd_cross_obv

Intraday nowcast — 1h-bar short-horizon (v6)

Next 24h nowcast
+0.11%
over next 24h on 1h bars
80% band
[-5.71%, +6.29%]
n_bars = 1729 · sigma_1h = 0.0095
Direction vs 30d ensemble
AGREES
1h direction: LONG · 30d direction: LONG
Source: intraday_forecaster_v10_trained_lgbm.
(trained model: 2026-05-26 (0d old), mean_directional_accuracy=0.523, n_features=17) Decision input only -- the 30d ensemble + factor regression remain the primary call. Conflicts surfaced into the Claude critique as horizon_conflict flag when |1h move| > 1%.

Meta-label gate — AFML Ch.3 secondary classifier (v6)

Verdict
meta-label: NEUTRAL
p_take = 0.51 · threshold 0.60
Bias adjustment
meta-label NEUTRAL (p_take=0.51 between 0.40 and 0.60) -- no adjustment.
Method: secondary LightGBM trained on (features + primary direction) -> P(primary is right). Source: meta_labeler_v10_trained_lgbm.
(trained model: 2026-05-26 (0d old), roc_auc=0.641, accuracy=0.608, n_train_rows=8,284) When ABSTAIN with p_take < 1-threshold AND bias non-neutral, the bias is demoted one bucket and a meta_abstain flag is added to the critique. See AFML Ch.3.6 (Lopez de Prado 2018).

Implied vol vs realized vol — options-trade gate (v8 W2)

Regime
NEUTRAL
no decisive vol mispricing — delta-1 setup over options
IV / RV ratio
0.96
z-score: n/a (insufficient history)
30d IV vs 30d RV
IV 40.3% (Polygon)
RV 42.2% (yang-zhang)
Provenance: source polygon_options:contracts_call; expiry 2026-06-26 (31d) · strike $395.00 · 1 strike(s) used.
Caveat: 15-min delayed end-of-day quotes; free-tier Polygon (no Greeks, no real-time). Regime is qualitative input only — NOT a numeric factor on the regression.

FMP fundamentals & analyst consensus (v7)

Quality / leverage

ROE 9.6%
ROIC -
FCF yield -
Debt / EBITDA -
Current ratio 1.75

Margins / valuation

Gross margin 64.5%
Operating margin 38.1%
Net margin 26.0%
P/E (TTM) 59.2
EV / EBITDA 32.3

Analyst consensus

Target mean -
Target high / low - / -
Upside vs last close -
Revisions score +0.000

Trade-bias signal — foundation for trade-guidance layer

Bias neutral
Composite z-score +0.202
Conviction 0.08079162777087381
Recommended playbook cash
Suggested position size 0% (no Kelly)
no Kelly: bias=neutral / not a conformal singleton (proxy off); singleton-proxy: news_activity_z=+0.00 (nonzero=False), wf30d_dir_acc=0.459214501510574 (>0.55=False)
Strategies on bias side
•Cash / no position
•Iron condor if IV rank > 50
•Wait for next factor refresh
Why this bias
composite_z = +0.20 | bias = neutral | conviction = 0.08 | macro_regime = risk_on_growth | ensemble = +0.19%

Sensitivity (OFAT tornado ±1 sd) and stress scenarios

FactorLoading wiTicker z-value+1 sd impact-1 sd impact
value_score +0.0495 -2.478 +0.0495 -0.0495
news_activity_score +0.0402 +0.000 +0.0402 -0.0402
momentum_score +0.0286 +2.674 +0.0286 -0.0286
revisions_score +0.0236 +3.000 +0.0236 -0.0236
quality_score +0.0192 -0.536 +0.0192 -0.0192
lowvol_score +0.0173 -0.367 +0.0173 -0.0173

Stress scenarios (forecast shift from base point)

ScenarioDescriptionStressed pointDelta vs base
rates_+100bps Yield curve +100bps (lowvol -1sd, value -0.5sd) -3.44% -4.20%
recession_risk_off Recession (momentum -1.5sd, lowvol +1sd, news -1sd) -5.82% -6.58%
quality_flight Quality flight (quality +1sd, revisions +1sd, momentum -0.5sd) +3.62% +2.86%

Multi-source live sentiment (free real-time)

Composite z-score -0.531
Active signals 3 of 3
Sources stocktwits, apewisdom, iv_skew
StockTwits bull 12
StockTwits bear 2
StockTwits net +0.71
Message volume 30
ApeWisdom mentions 1
24h change +0
Reddit rank 224
25-delta IV skew +2.0854
IV-skew read bearish

Analyst critique

Agreement with model agree_with_caveats
Confidence 0.4
PM one-liner ADI Technology: quant +0.19%/30d, disp +0.0034, no edge vs RW, macro neutral, 0 catalyst(s).
Sensitivity concern If value_score (the highest-loading factor) is mis-measured by +/-1 stdev, the bias likely flips.

What the model may have missed

Critique flags

Factor contribution methodology — where the numbers come from

Point return formula (linear factor model): r_hat = alpha + sum_i (w_i × f_i) where w_i is the cross-sectional loading for factor i (estimated from the cross-section of US large-cap names) and f_i is the z-scored factor value for this ticker (Grinold-Kahn winsorization at ±3).

Per-factor contribution shown in the waterfall above is exactly w_i × f_i (decimal-return units), so the bars sum (with intercept) to the linear forecast point. The ensemble point combines linear / Monte Carlo / AR(1) / random-walk per per-method-comparison table.

Bias mapping (composite z-score → LONG/NEUTRAL/SHORT): weighted sum of value (1.0), quality (0.7), momentum (1.0), low-vol (0.5), revisions (1.0), news-activity (0.6); thresholds ±1.0 with macro override (risk-off + LONG → reduce to NEUTRAL; risk-on-growth + SHORT → reduce to NEUTRAL). LONG → Playbook A (long-call / call-debit-spread / covered-call); SHORT → Playbook B (long-put / put-debit-spread / bear-call-spread); NEUTRAL → cash.

Sensitivity (one-factor-at-a-time tornado above): impact = w_i × 1sd per factor (MSCI / Two-Sigma Venn convention). Stress scenarios are canned multi-factor shocks (rates +100bps; recession risk-off; quality flight).

Factor decay uses exponential half-life per factor type: catalysts 7d, news 14d, revisions 30d, momentum 45d, value 90d, quality 90d (Tetlock 2007; Cohen-Malloy-Pomorski 2012). The heatmap above shows contribution × exp(-ln(2) × t / half_life) on a 5-day grid.

Factor IC backtest: Spearman rank correlation between each factor's cross-sectional ranking on day t and the realized h-day-forward return, aggregated across the panel (Grinold-Kahn 2000 ch.4 fundamental law of active management). Source for this report: synthetic_panel_252d_100tickers_seed42 (parallel runner).

Placebo audit (v6, GT-Score): GT-score = 0.47 passes falsification gate . Computed from 3 seed(s) across placebo kinds: shuffled, gaussian_iid, garch. Method: real directional accuracy = 53.3%; max placebo accuracy = 50.4%; AMG = +0.029. Source: placebo_audit_v6_ar1_runner. Provenance: arXiv 2604.15531 "Spurious Predictability in Financial ML" (Paper #3).

Catalysts in window (30d)

No catalysts within the forecast window.

Analyst narrative

Bull case

ADI ensemble forecast is +0.19% with 80% band [-8.52%, +9.97%] over 30 days. Positive drivers: momentum_score, revisions_score. 0 catalyst(s) in the window provide event-driven upside potential.

Bear case

Inter-method dispersion (+0.0034) and no clear edge vs. random-walk argue caution. Negative drivers: value_score. Macro regime risk_on_growth historically caps single-name conviction.

Synthesis

Weight the ensemble's +0.19% center against +0.0034 method dispersion. Risk On Growth regime + 0 catalyst(s) define the setup. Treat the 80% band as the working trade-sizing envelope.

Risk flags

Generated by Trade Identifier Forecast Layer v1.0 (dark mode). Ensemble methodology: linear multi-factor regression + GBM Monte Carlo + AR(1) + random-walk baseline. Factor decay: exponential half-life per factor type (Tetlock 2007; Cohen-Malloy-Pomorski 2012). Macro context: 10y / 3m Treasury yields + VIX z-score + sector ETF relative strength. Narrative source: template (deterministic template fallback). Not investment advice.