AAPL reports Q2 FY2026 EPS above consensus?
Market 52.0% against model 68.2%. Resolves in resolved, data updated 13d ago.
Decision layer
Actionable research signal
The model disagreement survives the current gates. This is still research context, not financial advice.
Expected value after costs, not raw probability spread.
How much support the model sees across available inputs.
Thin markets can erase apparent edge through spread and slippage.
Resolution ambiguity, timing, and data quality pressure the decision.
usable feature coverage.
Why / why not trade
One decision layer for the market read.
This public box mirrors the internal diagnostic style without exposing execution controls: decision, probability gap, cost-adjusted edge, blocker, and next thing to monitor.
side YES
68.2% model / 52.0% market
fees, spread, slippage, risk
Model edge survives the current public research gates.
Watch whether the market price moves toward or away from the model.
Read this market in three passes
Model 68.2% vs market 52.0%.
Raw disagreement is reduced by fees, spread, slippage, and risk controls.
Model leans YES
Why this read matters
The model-market gap currently survives the decision gates, but it is still research context and must be judged against the public track record.
AAPL reports Q2 FY2026 EPS above consensus?
Volume $144,400
Market-implied vs model probability
Factor attribution
The model estimates a 16-point higher probability than the market, primarily driven by historical base rate.
| FACTOR | SIGNAL | WEIGHT | LOG-ODDS ΔLog-odds contribution measures how much each factor shifted the model's probability estimate in log-odds space — the mathematically correct way to stack independent evidence. Formula: Δlog-odds = weight × signal. Positive values push the probability up; negative values push it down. Log-odds are converted back to probability via the logistic function at the end. | DIRECTION | DESCRIPTION |
|---|---|---|---|---|---|
| Historical base rate | 71% | — | +0.916 | Bullish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
| Cross-market divergence | —This factor was not available for this market. No approved cross-venue link exists for this market. | 0.20 | — | — | Whether the same event is priced differently on another venue. A gap may signal an opportunity or a structural difference. |
| 7-day price momentum | +0.06 | 0.35 | +0.021 | Neutral | 7-day drift of the market's own implied probability — sustained moves carry information. |
| BTC/ETH 7-day momentum | —This factor was not available for this market. This factor applies to crypto markets only. | 0.20 | — | — | 7-day Bitcoin or Ethereum return, normalized. Applied to crypto-category markets only. |
| Rate surprise | —This factor was not available for this market. This factor applies to Fed, CPI, and macro markets only. | 0.25 | — | — | 2-year Treasury yield reaction in the 48 hours after the most recent scheduled release — a proxy for how markets interpreted the data versus expectations. |
| Yield curve shift | —This factor was not available for this market. This factor applies to Fed, CPI, and macro markets only. | 0.15 | — | — | 30-day change in the 10-year minus 2-year Treasury spread. A flattening curve signals tightening expectations; steepening signals easing. |
| News signal | —This factor was not available for this market. No news signal available for this market in the past 14 days. | 0.25 | — | — | Reliability-weighted direction of relevant news from the past 14 days. Official sources (filings, agency statements) carry more weight than commentary. |
| Crowd forecast | —This factor was not available for this market. Insufficient forecasters to compute crowd signal. Requires at least 5 calibration-weighted estimates. | 0.20 | — | — | Calibration-weighted average of user probability estimates. Only applied when 5 or more weighted forecasters have submitted estimates. |
| Model probability | 71.9% | Prior: 71% · Market: 52.0% | |||
| Confidence (λ)Confidence λ (lambda) controls how much weight to give the model vs. the market. Formula: p_final = λ·p_model + (1−λ)·p_market. λ is derived from data quality, factor agreement, and liquidity. When inputs are weak, the model shrinks toward the market — not toward 50%. | 0.82 | Final: 68.2% = λ·model + (1−λ)·market | |||
Comparable eventshistorical base rate 71.4% - n=21
| Event | Date | Outcome | Prior mkt prob. |
|---|---|---|---|
| Nvidia Q3 FY2025 — Beats but softer guidance | 2024-11-20 | EPS $0.81 vs $0.74 est. Beat, but Q4 guidance midpoint slightly light. | 72% |
| Alphabet Q3 2024 — Search and Cloud beat | 2024-10-29 | EPS $2.12 vs $1.85 est. Google Cloud $11.4B vs $10.9B est. Beat. | 68% |
| Boeing Q3 2024 — Strike and write-downs miss | 2024-10-23 | EPS -$10.44 vs -$3.57 est. $6.2B loss from strikes and defense charges. Massive miss. | 35% |
| Apple Q3 FY2024 — Services record and iPhone beat | 2024-08-01 | EPS $1.40 vs $1.35 est. Services $24.2B all-time record. Beat. | 64% |
| Meta Q2 2024 — AI-driven ad revenue beat | 2024-07-31 | EPS $5.16 vs $4.72 est. Revenue $39.1B vs $38.3B est. Beat. | 68% |
| Intel Q2 2024 — Massive miss and 15,000 layoffs | 2024-07-25 | EPS $0.02 vs $0.10 est. Announced 15,000 layoffs and dividend cut. Miss. | 42% |
| Nvidia Q1 FY2025 — Blackwell transition beat | 2024-05-22 | EPS $6.12 vs $5.16 est. Revenue $26.0B vs $24.6B est. Beat. | 75% |
| Alphabet Q1 2024 — First-ever dividend + buyback | 2024-04-25 | EPS $1.89 vs $1.51 est. Beat + $70B buyback + first dividend. | -- |
| Tesla Q1 2024 — Delivery and margin miss | 2024-04-23 | EPS $0.45 vs $0.51 est. Revenue $21.3B vs $22.3B est. Miss. | 45% |
| Goldman Sachs Q1 2024 — Trading revenue beat | 2024-04-15 | EPS $11.58 vs $8.73 est. FICC and equities trading dominated. Beat. | 60% |
| Meta Q4 2023 — First dividend + massive efficiency beat | 2024-02-01 | EPS $5.33 vs $4.82 est. Revenue $40.1B vs $39.2B est. First dividend announced. Beat. | 68% |
| Amazon Q4 2023 — AWS re-acceleration beat | 2024-02-01 | EPS $1.00 vs $0.80 est. AWS grew 13%, re-accelerating. Beat. | 65% |
Real historical events from the comparable-events library (showing 12 of 21 matched). The model's base rate is the realized frequency over the full matched set.
Scenario treeEngine template
Node probabilities are conditional on the parent; hover for cumulative path probability. Leaf EV is per $1 YES contract at the current price, before fees (fee-adjusted EVs in the table on the left).
| Path | Path prob. | YES pays | EV (YES, after costs) |
|---|---|---|---|
| Threshold hit in first half of window | 30.7% | $1 | +44.9c |
| Threshold hit in second half | 37.5% | $1 | +44.9c |
| Never reaches threshold in window | 31.8% | $0 | -55.1c |
Root-implied probability 68.2% reconciles with the model's 68.2% (±1pt invariant).
Why this mattersTemplate (no LLM key)
A 16.2% probability gap at a 52.0% price translates to 13.1% expected value per dollar of payout exposure after costs on the YES side. EV — not the raw probability gap — is the comparable number: the same gap is worth very different amounts at 50¢ and at 92¢.
What could make this wrongTemplate (no LLM key)
The model's edge depends on its inputs being right. Concretely: the base rate of 71.4% may not apply if this event differs structurally from its reference class; the pm.momentum_7d factor could be noise rather than information at this horizon; and with confidence at 0.82, the model itself concedes meaningful estimation error. Resolution risk remains: the contract pays on the precise criteria — "Resolves YES if Apple reports Q2 FY2026 diluted EPS above the consensus estimate published by Bloomberg at market close on the day before th…" — not on the thesis.
- - Risk score 34/100 — composite of liquidity, volatility, time-to-resolution, data quality and category risk.
- - Factor agreement 1.00: factors broadly agree, but shared blind spots are possible.
- - Data quality 0.64 (simulated input in MVP).
- - Simulated model values — this brief demonstrates structure, not live research.
Description
Apple Q2 FY2026 earnings. The model sees a small edge but below the tradeable hurdle.
Resolution criteria (verbatim, with analyzer flags)
analyzed by heuristicResolves YES if Apple reports Q2 FY2026 diluted EPS above the consensus estimate published by Bloomberg at market close on the day before the earnings call.
Resolves Fri, 19 Jun 2026 03:48:52 GMT. The contract pays on these exact criteria, not on the thesis.
Suggested paper position
Paper position only. No real-money execution
Live open-market tracking
Since the first stored model read on 2026-06-09, the market has moved from 52.0% to 52.0%.
This is a directional diagnostic for unresolved markets, not final performance. Resolved outcomes still determine the official live record.
Data quality64/100 - usable
Missing: Cross-market divergence, News signal, Crowd forecast
When features are unavailable, the model increases uncertainty and weights the final estimate closer to the market price. Lower data quality does not mean the market is wrong. It means the model is being appropriately humble.
Risk factor breakdownsim
| Inverse liquidity | 24 | |
| Price volatility | 34 | |
| Resolution proximity | 100 | |
| Data quality | 55 | |
| Category base risk | 40 | |
| Resolution ambiguity | 8 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 0 |
Composite score 34/100, higher = riskier.
Related markets
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| BTC closes above $100k this week? same event: same venue event + wording overlap | 61.0% | -4pt |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.