GOOGL · Bayesian revenue outlook
Alphabet Inc.: possible revenue paths
Model computed 2026-11-04 · Data cutoff 2026-09-30
Latest verified revenue: $127.577B for the quarter ended 2026-09-30. Reported source.
Forecasts are conditional on the listed data cutoff. Sources were refreshed for this model run on 2026-11-04; the cutoff above identifies the latest verified revenue observation included in the fit. Some forecast quarters may already have ended by the computation date. Read each target date before treating an estimate as a future-quarter outlook.
PyMC seasonal AR(1) quarterly log-revenue growth with Student-t shocks; posterior predictive paths include parameter uncertainty and new shocks at every horizon.
A revenue-history baseline, conditional on its assumptions. These are posterior predictive intervals for actual revenue, not confidence bands for a fitted curve. Management guidance is not a probability bound. The model does not identify customer-specific pricing, demand shocks or causal expense effects.
Each line is one possible future revenue path. The 80% and 95% intervals are pointwise model probabilities, not simultaneous coverage for the whole path. The median is not an expected dollar mean. 1 sampled paths extend beyond the displayed chart range; the plotted intervals use the full simulations. Open full-size chart.
USD · four quarters after the listed data cutoff, not necessarily after today
| Quarter ending | Predictive median | 80% predictive interval | 95% predictive interval |
| 2026-12-31 | $146.634B | $141.206B–$152.164B | $137.612B–$156.687B |
|---|
| 2027-03-31 | $138.278B | $129.684B–$147.793B | $124.106B–$154.135B |
|---|
| 2027-06-30 | $146.333B | $134.020B–$160.255B | $126.065B–$170.406B |
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| 2027-09-30 | $152.996B | $137.374B–$171.002B | $127.240B–$185.154B |
Future period-end dates are approximate: month-end issuers retain month-end dates; weekly issuers advance by 13 weeks. Future 53-week adjustments are not known.
Historical forecast checks
Each historical cutoff refits the model using only earlier observations. Across the available outcomes, the 80% intervals covered 15/16 and the 95% intervals covered 16/16. Small samples and overlapping outcomes do not establish nominal coverage; covering every outcome can indicate overly wide intervals.
| Horizon | Cases | Bayesian median MAPE | Last reported revenue MAPE | Same quarter last year MAPE | 80% covered | 95% covered |
|---|
| 1 quarter | 4 | 3.26% | 9.72% | 9.66% | 3/4 | 4/4 |
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| 2 quarters | 4 | 3.28% | 3.71% | 11.13% | 4/4 | 4/4 |
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| 3 quarters | 4 | 2.58% | 9.98% | 12.55% | 4/4 | 4/4 |
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| 4 quarters | 4 | 2.67% | 14.14% | 14.14% | 4/4 | 4/4 |
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All point-forecast errors use the same historical cases. A simple baseline may have lower error than the Bayesian median; this rollout does not establish that the Bayesian model is superior for every company.
Up to four historical cutoffs spaced four quarters apart, with at least 16 training quarters; full four-quarter outcomes required. Fixed specification, no winner selection.
These are retrospective checks using latest-restated data, not forecasts archived before their outcomes. Results from DDOG or another company are not transferred to this company.
Sampling diagnostics and limitations
Maximum R-hat 1.001 · minimum bulk ESS 4793 · minimum tail ESS 2652 · divergent transitions 0. The required sampling checks passed. These diagnose computation, not predictive calibration.
Fixed priors
mu is long-run quarterly log growth; phi is growth persistence; sigma is the shock scale; season gives quarterly effects; shock_df controls tail thickness.
| Parameter | Prior / fixed assumption |
|---|
| mu | Normal(0,0.10) |
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| phi | Normal(0,0.5) truncated to [-0.98,0.98] |
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| sigma | HalfNormal(0.10) |
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| season | 4 Normal(0,0.15), centered to sum zero |
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| shock_df | 5 |
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Future regime changes and uncertainty over alternative model structures remain outside these intervals. The model should be scored on subsequent releases, and its forecast vintage preserved.
- Revenue-history baseline; does not identify customer-level discounts, acquisitions or future structural breaks.
- Intervals are pointwise, conditional on this model and priors, not guaranteed coverage or simultaneous path bounds.
- Latest-restated historical data; retrospective tests are not archived real-time forecasts. Small test samples cannot validate nominal coverage.
- Student-t log shocks can make dollar means undefined; point forecasts are medians.
- Sources were freshly acquired for this run. Each issuer has its own latest reported period; preliminary ranges are not treated as exact actual revenue.
Management guidance versus reported revenue
No numerical quarterly consolidated-revenue range located in sampled earnings releases. Capital expenditure outlooks are a different metric.
No verified numerical quarterly consolidated-revenue guidance is plotted for this research sample. This does not establish that the company never provides guidance; annual, segment-only and qualitative outlooks are separate.
Preserved Bayesian forecast vintage
Computed 2026-11-04 using revenue through 2026-09-30. These original numbers are retained unchanged to allow subsequent scoring; they were not refitted with the new results. Forecasts computed after a target quarter ended are retrospective estimates, not pre-release predictions.
Original predictive medians and intervals
| Quarter ending | Original median | Original 80% interval | Original 95% interval |
|---|
| 2026-12-31 | $146.554B | $141.253B–$152.281B | $137.574B–$156.618B |
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| 2027-03-31 | $138.320B | $129.822B–$147.711B | $124.368B–$154.199B |
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| 2027-06-30 | $146.496B | $133.984B–$160.295B | $126.315B–$169.749B |
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| 2027-09-30 | $152.962B | $136.976B–$171.179B | $128.030B–$183.103B |
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Open preserved spaghetti chart
Earlier company analysis · preserved vintage 2026-10-29The report below retains its original forecasts, validation and company-specific discussion. Those revenue estimates use a different model or information cutoff; they are separate from the Bayesian outlook above. Any EPS model below has not been recalculated using the new Bayesian revenue paths.
GOOGL · Revenue & earnings intelligence
Growth is changing.
Earnings need a separate lens.
Forecast issued 2026-10-29 · Data through 2026-09-30 · 49 revenue quarters · All available quarters included in final refit
Earlier summary (2026-10-29): Alphabet's Q3 revenue reached $127.58B. The updated model allows the underlying growth rate to rise or fall, while the earnings model separates operating margins, investment gains, taxes, preferred dividends and diluted shares.
Next four quarters · revenue$584.4B+24.1% versus the preceding four quarters
Q3 reported diluted EPS$2.12Includes an $8.66B equity investment loss
Old Q3 revenue forecast error6.17%Underestimated actual revenue
What changed after earnings
The October 14 forecast was $119.71B, with a $114.93B–$124.48B range. Actual revenue was $127.58B, outside that range. Its estimation sample ended in Q1: Q2 remained withheld even for forward forecasts. The revised forecast refits through Q3 after chronological validation.
AI is a hypothesis, not a measured causal effect. Cloud grew 103% year over year, compared with 12% for Search. AI demand could help explain acceleration, but this aggregate time trend also absorbs pricing, product mix, acquisitions, currency and other changes. It cannot isolate AI's contribution.
Predictions to check at the next four earnings releases
These predictions are frozen as of October 29. Revenue is in billions of dollars; EPS is diluted GAAP dollars per share. Ranges are approximate 95% prediction ranges estimated from historical forecast errors.
| Fiscal quarter / period end | Revenue | 95% revenue range | YoY | EPS | 95% EPS range |
Q4 FY2026 2026-12-31 | $145.35B | $123.80–$170.65B | +27.7% | $3.10 | $-1.61 to $7.82 |
Q1 FY2027 2027-03-31 | $137.76B | $114.06–$166.38B | +25.4% | $2.94 | $-2.24 to $8.13 |
Q2 FY2027 2027-06-30 | $145.91B | $118.11–$180.24B | +21.8% | $3.12 | $-2.40 to $8.64 |
Q3 FY2027 2027-09-30 | $155.40B | $121.18–$199.29B | +21.8% | $3.32 | $-2.65 to $9.29 |
A growth rate that can evolve
We compare seasonal growth, a fixed log-linear trend with quarterly effects, and three smooth time-varying trends. The selected model is dynamic_16. The dynamic candidates fit log(revenue) = trend + quarter effect + error. A penalty on second differences of the trend shrinks unnecessary changes in growth, while permitting persistent acceleration. Future growth gradually returns toward its recent eight-quarter average; acceleration is not extrapolated indefinitely.
At every historical forecast origin, a separate inner chronological test chooses the model using only earlier outcomes, across horizons one through four. The final choice is refitted on all observations through Q3. This avoids selecting a model on training fit or on the latest miss alone.
| Revenue candidate | Fixed-candidate MAPE, pooled horizons |
|---|
| seasonal_growth | 7.74% |
| log_trend | 11.80% |
| dynamic_16 · selected for new forecast | 5.13% |
| dynamic_64 | 6.03% |
| dynamic_256 | 7.10% |
Unpacking the $2.12 EPS result
EPS = (operating income + equity gains/losses + other non-operating income − income taxes − preferred dividends) ÷ diluted shares. Q3 diluted shares were 12.368 billion.
| Q3 determinant | Amount ($B) | EPS contribution |
|---|
| Operating income | 40.576 | $3.281 |
| Equity investment gains / losses | -8.664 | $-0.701 |
| Other non-operating income excluding equity | 0.443 | $0.036 |
| Income taxes | 5.887 | $-0.476 |
| Preferred dividends | 0.298 | $-0.024 |
Taxes and preferred dividends are deductions. This exact pre-rounding accounting bridge differs from a hypothetical after-tax add-back. Alphabet separately disclosed that the equity loss reduced EPS by $0.55 after its associated tax benefit.
EPS forecast assumptions and sensitivities
Selected EPS model: components_0.8. Component candidates exponentially smooth operating margins and non-equity other income, use the median effective tax rate of the last eight quarters, and hold diluted shares and preferred dividends at their latest levels. They assume zero net equity investment gains or losses. A seasonal EPS baseline is also tested.
The component scenario is conditional on neutral investment marks; it is not an assertion that investment gains have an expected value of zero. The broad GAAP ranges include historical investment shocks. They may extend below zero and do not bound every possible valuation shock.
| Quarter | Operating margin | Operating profit ($B) | Tax rate | EPS with neutral equity marks |
|---|
| Q4 FY2026 | 0.323 | $46.94 | 0.179 | $3.10 |
| Q1 FY2027 | 0.323 | $44.49 | 0.179 | $2.94 |
| Q2 FY2027 | 0.323 | $47.12 | 0.179 | $3.12 |
| Q3 FY2027 | 0.323 | $50.19 | 0.179 | $3.32 |
Margin and tax rates are proportions (0.320 = 32%). Other non-equity income, preferred dividends and diluted shares are held to the documented component assumptions.
For the next quarter, holding other inputs fixed: an extra $1B of revenue adds about $0.021 EPS; one percentage point of operating margin adds $0.096; a $10B pre-tax equity gain or loss changes EPS by roughly ±$0.66 using the assumed tax rate. More diluted shares reduce positive EPS proportionately.
| EPS candidate | Fixed-candidate MAE ($/share), pooled horizons |
|---|
| components_0.2 | $1.27 |
| components_0.5 | $1.21 |
| components_0.8 · selected | $1.19 |
| seasonal_eps | $1.35 |
Validation and limits
The tables above describe each fixed candidate. The table below evaluates the complete selection procedure, choosing afresh at each origin. Revenue targets span Q3 2022–Q3 2026; reported EPS targets span Q1 2023–Q3 2026. These are different comparisons; the final winner’s historical error is not the error of the selection procedure.
| Quarters ahead | Revenue tests | Revenue MAPE | EPS tests | EPS MAE |
|---|
| 1 | 17 | 6.32% | 12 | $1.11 |
| 2 | 16 | 7.57% | 11 | $1.24 |
| 3 | 15 | 8.64% | 10 | $1.34 |
| 4 | 14 | 10.56% | 9 | $1.53 |
These are retrospective tests using latest-restated filings. The method was designed after seeing Q3, so these tests are not independent prospective evidence. Horizon tests overlap and are not independent samples. Prediction ranges use horizon-specific RMS errors and Student-t scaling; small samples, regime changes and model selection prevent a guaranteed 95% coverage claim.
Older diluted shares are sometimes inferred from rounded EPS. Missing Q4 shares are approximated using annual and quarterly duration-weighted averages; Q4 EPS reconstructed this way is excluded from EPS scoring. EPS is never derived by subtracting cumulative EPS. These limitations affect the EPS training history; the latest quarter uses reported shares and EPS.
How future results will be scored
Compare each frozen target with the first reported consolidated revenue and diluted GAAP EPS for that period. Record signed errors, revenue absolute percentage error, EPS absolute error, and whether each 80% and 95% range covered the result. Reconcile EPS misses to operating margin, investment marks, other income, tax, preferred dividends and diluted shares. Keep restatements separately; do not replace this vintage with a refit. No earnings announcement dates are assumed.