TXN — Texas Instruments Incorporated

Report date: 2026-05-26  |  Sector: Technology  |  Last price: $309.21  |  Horizon: 30d  |  Generated: 2026-05-26T07:21:20.706204Z

Forecast summary

Ensemble point -0.00%
80% CI [-9.81%, +11.23%]
95% CI [-14.41%, +17.74%]
Method dispersion 0.0035
Beats RW baseline NO
MC drift (annual) 4.29%
MC sigma (annual) 42.33%
MC paths 1000
Bull target (90th pct) +19.43% -> $369.30
Base target (50th) -0.46% -> $307.78
Bear target (10th pct) -17.55% -> $254.95
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) +36.88%

Forecast plot (interactive)

Realised volatility

Yang-Zhang annualized (60d) 42.33%
Close-to-close annualized (60d) 48.13%

Per-method comparison

MethodWeightPoint80% lo80% hi95% lo95% hi
linear 25.0% +0.51% -3.17% +4.17% -4.75% +6.18%
monte_carlo 25.0% -0.46% -17.55% +19.43% -25.64% +30.81%
ar1 25.0% -0.06% -3.07% +3.04% -4.63% +4.72%
random_walk 25.0% +0.00% -15.45% +18.27% -22.63% +29.25%

Factor contributions (interactive waterfall)

Factor contribution table

FactorLoadingTicker valueContribution
value_score +0.0495 -2.0631 -0.1021
quality_score +0.0192 +1.7347 +0.0334
momentum_score +0.0286 +2.2132 +0.0633
lowvol_score +0.0173 -0.9064 -0.0157
revisions_score +0.0236 +1.0650 +0.0252
news_activity_score +0.0402 +0.0374 +0.0015
(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 $281.41B
P/E (trailing) 52.9
P/B 16.8
Forward P/E 32.8
PEG 1.48
Dividend yield 184.00%
Beta 1.30
52w high / low $315.57 / $152.73
Distance from 52w high -2.02%
Cross-sectional rank 55 / 92 median
Panel source (trained model: 2026-05-26 (0d old), universe_size=92, lookback_days=252)
RSI(14) 72.0
SMA50 / SMA200 $241.24 / $198.63
ATR(14) $10.33
Avg volume (20d) 7.53M
Profit margin 29.11%
ROE 32.35%
Revenue growth (YoY) +18.60%
Earnings growth (YoY) +31.30%
Debt/Equity 83.7
Current ratio 4.46
Short ratio 2.02

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

Horizonn predictionsDirectional accuracyMAE (return)RMSE80% CI hit ratePearson(pred, real)
1d 691 53.4% 1.51% 2.28% 83.1% +0.021
30d 662 49.1% 11.96% 16.16% 69.9% -0.189
60d 632 46.8% 16.36% 22.50% 70.3% -0.210

Volume momentum (Granville / CGW / Quong-Soudack)

Composite z +0.965
Active signals 7 of 7
MFI(14) 61.67
CMF(20) +0.1981
OBV z (252d) +2.677
VPT z (252d) +2.600
VW-momentum z +0.261
Volume z (60d) +0.013
Relative volume (vs 20d ADV) 0.95x
CMF z (252d) +0.941

Sector rotation & AI-spillover (v6)

Sector ETF XLK
Rel-return 5d / 20d / 60d -0.20% / -0.40% / +13.20%
Sector mom-z 1m / 3m / 6m +2.27 / +2.72 / +1.64
Rotation phase cyclical
AI-factor beta (60d) +0.017
AI spillover score +0.0016
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 +0.00 (9 peers)
P/E percentile
44% (44% cheaper than this)
20d momentum percentile
44% (44% lag this)
Market-cap percentile
56%
Peer set (mcap band 0.2x-5x, same sector)
QCOM KLAC ARM PLTR IBM AMAT SNDK PANW LRCX
9 peers in Technology (mcap band 0.2x-5x); signal=mixed; score=+0.00
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 / 6 sell / 7 neutral · net -7.0
1d verdict
NEUTRAL
3 buy / 6 sell / 8 neutral · net -3.5
1h verdict
NEUTRAL
4 buy / 1 sell / 12 neutral · net +6.0

1wk NEUTRAL 4/6/7

RSI(14) 81.6
MACD hist +11.1338
Bollinger %b 1.00
ADX(14) 31.3 RISING
ATR % 5.82%
MFI(14) / CMF(20) 71.7 / +0.173
Donchian pos / break 0.95
vs SMA200 ABOVE
n_bars521

1d NEUTRAL 3/6/8

RSI(14) 71.8
MACD hist -1.5006
Bollinger %b 0.84
ADX(14) 53.5
ATR % 3.35%
MFI(14) / CMF(20) 55.0 / +0.198
Donchian pos / break 0.88
vs SMA200 ABOVE
n_bars1253

1h NEUTRAL 4/1/12

RSI(14) 57.9
MACD hist +1.0438
Bollinger %b 0.70
ADX(14) 19.9
ATR % 1.14%
MFI(14) / CMF(20) 53.5 / +0.118
Donchian pos / break 0.69
vs SMA200 ABOVE
n_bars1729

Cross-timeframe confluence

Confluence LONG (0-1) 0.20
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
+0.49%
over next 24h on 1h bars
80% band
[-4.86%, +6.14%]
n_bars = 1729 · sigma_1h = 0.0087
Direction vs 30d ensemble
AGREES
1h direction: LONG · 30d direction: SHORT
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 = 0.56 · threshold 0.60
Bias adjustment
meta-label NEUTRAL (p_take=0.56 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
1.26
z-score: n/a (insufficient history)
30d IV vs 30d RV
IV 52.0% (Polygon)
RV 41.2% (yang-zhang)
Provenance: source polygon_options:contracts_call; expiry 2026-06-26 (31d) · strike $310.00 · 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 32.3%
ROIC -
FCF yield -
Debt / EBITDA -
Current ratio 4.46

Margins / valuation

Gross margin 57.3%
Operating margin 37.8%
Net margin 29.1%
P/E (TTM) 52.9
EV / EBITDA 33.5

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 +0.140
Conviction 0.05603690139038836
Recommended playbook cash
Suggested position size 0% (no Kelly)
no Kelly: bias=neutral / not a conformal singleton (proxy off); singleton-proxy: news_activity_z=+0.04 (nonzero=True), wf30d_dir_acc=0.4909365558912387 (>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 = +0.14 | bias = neutral | conviction = 0.06 | macro_regime = risk_on_growth | ensemble = -0.00%

Sensitivity (OFAT tornado ±1 sd) and stress scenarios

FactorLoading wiTicker z-value+1 sd impact-1 sd impact
value_score +0.0495 -2.063 +0.0495 -0.0495
news_activity_score +0.0402 +0.037 +0.0402 -0.0402
momentum_score +0.0286 +2.213 +0.0286 -0.0286
revisions_score +0.0236 +1.065 +0.0236 -0.0236
quality_score +0.0192 +1.735 +0.0192 -0.0192
lowvol_score +0.0173 -0.906 +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) -3.69% -4.20%
recession_risk_off Recession (momentum -1.5sd, lowvol +1sd, news -1sd) -6.07% -6.58%
quality_flight Quality flight (quality +1sd, revisions +1sd, momentum -0.5sd) +3.37% +2.86%

Multi-source live sentiment (free real-time)

Composite z-score -0.436
Active signals 3 of 3
Sources stocktwits, apewisdom, iv_skew
StockTwits bull 7
StockTwits bear 0
StockTwits net +1.00
Message volume 30
ApeWisdom mentions 1
24h change +0
Reddit rank 211
25-delta IV skew +2.5019
IV-skew read bearish

Analyst critique

Agreement with model agree_with_caveats
Confidence 0.4
PM one-liner TXN Technology: quant -0.00%/30d, disp +0.0035, 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 = 53.4%; max placebo accuracy = 50.6%; AMG = +0.028. 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

TXN ensemble forecast is -0.00% with 80% band [-9.81%, +11.23%] over 30 days. Positive drivers: momentum_score, quality_score. 0 catalyst(s) in the window provide event-driven upside potential.

Bear case

Inter-method dispersion (+0.0035) 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 -0.00% center against +0.0035 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.