GOOG Fair Value Estimate
Is Alphabet Inc - Class C (GOOG) fairly priced at $338.89? We used 3 separate valuation methods on real SEC data. Here's what they show.
All 3 models say it's worth around
$273.43
Composite fair value (average of 3 models)
19% above fair valueFair value
$273.43
Market price
$338.89
What would I earn buying today?
(CAGR)
-4.2%
per year
What's a safe entry price?
(margin of safety)
$232.41
15% buffer below fair value
Do the models agree?
(model consensus)
2/3
overvalued
How we got this number
Each model asks a different question about GOOG's value. Tap any one to see the exact math — every number comes from a real SEC filing.
2 of 3 models say overvalued. The Earnings-Based DCF gives a more favorable view because projected earnings growth leads to a higher value than simpler models capture.
Think these models are too simple?
They are — on purpose. For deeper analysis using free cash flow, growth decay, and terminal value, try the full DCF Calculator. Or let X-Ray guide you through a full 5-step investment review.
About the Fair Value Calculator
This tool estimates intrinsic value using three independent models: the Graham Number (earnings × book value), a PEG-Adjusted fair P/E approach, and an Earnings-Based DCF that projects future earnings. All three are averaged for a composite fair value with upside or downside versus market price.
Using multiple models matters — one formula never tells the full story. When all three point in the same direction, the signal gains weight.
How It Works
Graham Number: sqrt(22.5 × EPS × Book Value) — a conservative upper bound based on earnings and net asset value.
PEG-Adjusted: Computes a fair P/E by matching the growth rate (PEG benchmark of 1.0), then applies that to current earnings.
Earnings-Based DCF: Projects future earnings, prices them using the sector median P/E, then discounts back to today.
The composite averages all three equally. Model fitness ratings tell you which results to trust most for this stock.
Is Alphabet Inc - Class C Fairly Priced?
ExampleThree valuation methods were applied to Alphabet Inc - Class C (GOOG) using live SEC filing data. Each one asks a different question — and they don't always agree.
Graham Number — Benjamin Graham's formula: sqrt(22.5 × EPS × Book Value). For GOOG with EPS of $10.81 and book value of $34.41, the Graham Number lands at $$91.49. This model was designed for asset-heavy firms — it often sets a low floor for asset-light companies.
PEG Ratio — Peter Lynch's insight: a stock's P/E should match its growth rate. GOOG grows earnings at 20.0% per year, so a fair P/E of 20.0x gives a PEG-adjusted fair value of $$216.20. The market P/E of 30.9x is higher than what growth justifies.
Earnings-Based DCF — Projects earnings 5 years forward at 20.0%, prices the future stock using the Technology sector median P/E of 28x (not GOOG's own inflated multiple), then discounts back at 8%. Result: $$512.59.
| Model | Fair Value | vs. Market Price ($338.89) |
|---|---|---|
| Graham Number | $91.49 | 270% above |
| PEG-Adjusted | $216.20 | 57% above |
| Earnings-Based DCF | $512.59 | 34% below |
Two of three models agree on direction. Earnings-Based DCF disagrees — projected earnings growth leads to a higher value than simpler models capture. This is common and doesn't invalidate the signal — check the model fitness ratings above to see which results fit GOOG best.
Frequently asked questions
The Fair Value Calculator runs three separate models on every S&P 500 stock. The Graham Number uses earnings and book value to find a safe price floor. The PEG Ratio checks if the P/E ratio matches earnings growth. The Earnings-Based DCF projects future earnings and brings them back to today's value. We average all three for a combined fair value, and show how much they agree.
Try it now — run all three valuation models for GOOG with live financial data.
Back to calculatorAll data from Alphabet Inc - Class C SEC filings via Tiingo · Calculations by GoodMoat · Last refreshed Apr 25, 2026
This is not financial advice. Fair value models are estimates based on past data and assumptions.