Meta Platforms Inc.
META
Meta Platforms, Inc. develops products that enable people to connect and share with friends and family through mobile devices, PCs, virtual reality headsets, wearables and home devices around the world. The company is headquartered in Menlo Park, California.
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.
-15.1% vs fair value (5th pct of mega caps)
-32.1
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.
+35.2% expected
+23.5
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.
-0.24
+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 +18%, margin 35%, FCF yield +3.1%
+10.0
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 21.4 vs 25.6 avg (-0.6σ)
+3.0
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.
+38.5% 30d
+4.7
Volatility
weight 0.03
An annualized volatility penalty. High volatility lowers the score; low volatility never raises it.
0.40 ann.
-0.5
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Cyclical regression model price trajectory and target range, updated each trading day.
Seasonality
Historical seasonal patterns across monthly and weekly windows to contextualize current timing.
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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.