GOOGLCOMMUNICATION SERVICESFree preview

Alphabet Inc Class A

Last close: $330.65Last updated: Sep 9, 2026

GOOGL

— Alphabet Inc Class A

INDUSTRY:INTERNET CONTENT & INFORMATION
SECTOR:COMMUNICATION SERVICES

Alphabet Inc. is an American multinational conglomerate headquartered in Mountain View, California. It was created through a restructuring of Google on October 2, 2015, and became the parent company of Google and several former Google subsidiaries. The two co-founders of Google remained as controlling shareholders, board members, and employees at Alphabet. Alphabet is the world's fourth-largest technology company by revenue and one of the world's most valuable companies.

OVERALL AI RATING

58/100

BULLISH

75% confidence · 8 of 8 factors

Higher when more factors have data and they agree with each other.

Bullish outlook primarily supported by favorable momentum indicators. Tempered by minor heavy historical seasonal headwinds.

FUNDAMENTALS OUTLOOK

67

/100

Favorable

+0% vs the model's 6-month fair value; ranks in the bottom 46% of mega caps by model upside.

Valuation against the model's 6-month target, reported financials, P/E versus this company's own history, and analyst consensus.

Fair Value

weight 0.3

+0.1% vs fair value (46th pct of mega caps)

Fundamentals

weight 0.12

revenue +12%, margin 34%, FCF yield +1.0%

P/E vs History

weight 0.08

P/E 16.6 vs 24.9 avg (-2.2σ)

Analyst Consensus

weight 0.08

consensus

SEASONALITY OUTLOOK

37

/100

Soft

Historically poor performance with expected drop of -10.8%.

The seasonal price model at both scored horizons.

Seasonal Forecast · 90d

weight 0.2

-1.7% expected

Seasonal Forecast · 30d

weight 0.04

-10.8% 30d

TECHNICAL OUTLOOK

50

/100

Neutral

Neutral market momentum and balanced indicators.

The volatility penalty. The chart classifier's short-horizon read is shown for reference but no longer weighs on the score.

Chart Signal

informational · no weight

+0.11

Volatility

weight 0.03

0.31 ann.

How the rating is built — each factor's weight × signal contributes to the composite; the contributions sum to the overall score. A factor with no data counts as neutral, so it neither helps nor hurts.

Fair Value

weight 0.3

How far today's price sits from the model's 6-month fair value estimate, ranked against companies of similar size.

+0.1% vs fair value (46th pct of mega caps)

-3.1

Seasonal Forecast · 90d

weight 0.2

The seasonal price model projected 90 days out, as an expected return. It reads this stock's own price history and repeating calendar cycles — not company news, earnings, or business quality. Same model as the 30-day factor below, read at a longer horizon.

-1.7% expected

-2.6

Chart Signal

informational · no weight

A machine-learning classifier reading momentum and trend structure across daily and weekly price bars. Needs about 5 years of trading history. Shown for information only: it reads roughly five days ahead, shorter than the score's horizon, so it carries no weight in the AI Score.

+0.11

+0.0

Fundamentals

weight 0.12

Reported results, not projections: revenue growth, operating margin, and free cash flow measured against market value. Loss-making or cash-burning companies score negative here.

revenue +12%, margin 34%, FCF yield +1.0%

+7.6

P/E vs History

weight 0.08

Today's price-to-earnings against this company's own trailing average, in standard deviations. Needs positive earnings.

P/E 16.6 vs 24.9 avg (-2.2σ)

+9.4

Analyst Consensus

weight 0.08

Wall Street consensus ratings, weighted by conviction.

consensus

+9.4

Seasonal Forecast · 30d

weight 0.04

The same seasonal price model as the 90-day factor above, read 30 days out. A near-term and a medium-term view of one forecast, which is why they can disagree.

-10.8% 30d

-4.7

Volatility

weight 0.03

An annualized volatility penalty. High volatility lowers the score; low volatility never raises it.

0.31 ann.

+0.0

Methodology & trust

What this is (and isn’t)

These outputs are generated by machine learning models trained on historical price, fundamental, and volume data. The models summarize historical data and current model outputs — they do not predict the future or constitute personalized investment advice. All figures are updated on a regular cadence and reflect the most recent available data at time of generation.

ŷRobot provides research and information, not personalized financial advice. Past performance is not a guarantee of future results.