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ABNB

AirbnbC
Nasdaq / Consumer Services
Last Price
At close
2026-07-20
View Chart
Current thesis
The bull read is that Airbnb delivered a clean top-line beat, raised 2026 guidance, showed strong North America and Latin America momentum, and highlighted monetization levers from fee simplification, insurance programs, services, experiences, hotels, and AI efficiency. Secondary analyst-aggregation data after the print showed several higher price targets on May 8, 2026, suggesting the buy side did not read the quarter as thesis-breaking.
Posture
Mixed
Lead driver
Value
What changed
Value remains the lead driver in the composite, 7D delta -0.1.
What can break
Management expects tougher second-half comparisons tied to the 2025 Reserve Now, Pay Later rollout, which could make growth acceleration harder to sustain.
Momentum
62
Value
49
Sentiment
43
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $145.00 · Bull $165.00 · Bear $118.00
Data freshness
Prices
As of 2026-07-20
Fundamentals
As of 2026-07-17 • Vendor: Data Vendor v1
Scores
As of 2026-07-20 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-09 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-07-20
Supporting evidence
What
Grade C · Mixed
Confidence Medium · Net Neutral
Target $156.64
Why
Momentum62 · Δ7d +7.5
Value49 · Δ7d -0.1
Sentiment43 · Δ7d -1.7
So what
Balanced signals (Net Neutral). Wait for confirmation before sizing up.
Lead driver: Value · See fundamentals
Momentum
62
26% active weight
Current posture
7d trendImproving
Δ7d
+7.5
Δ21d
+7.3
Value
49
39% active weight
Current posture
7d trendFlat
Δ7d
-0.1
Δ21d
+0.1
Sentiment
43
34% active weight
Current posture
7d trendSoftening
Δ7d
-1.7
Δ21d
-2.0
Why this grade

Composite grade C. Momentum 62.3 / Value 48.7 / Sentiment 43.5

Fundamentals (TTM)
As of 2026-07-17
Market Cap
$87.98B
Beta
1.15
Shares Out
593.5M
P/E (TTM)
32.3
P/S (TTM)
6.90
P/FCF (TTM)
17.96
Rev YoY
+17.9%
EPS YoY
+7.3%
Gross Margin
+72.4%
Op Margin
+22.6%
Net Debt
-$8.78B
Current Ratio
1.44
As of 2026-07-20 • Updated nightlySource: Internal modelMethodology