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LYFT

LyftD
Nasdaq / Transportation
Last Price
At close
2026-06-02
View Chart
Current thesis
The primary-source bull case is that Lyft is still showing real operating improvement: Q1 active riders rose 17% to 28.3M, gross bookings rose 19% to $4.946B, adjusted EBITDA rose 25% to $132.8M, and trailing-12-month free cash flow reached $1.1B, while Q2 bookings guidance implies continued double-digit growth. [#8-K-2026-05-07]
Posture
Defensive
Lead driver
Sentiment
What changed
Sentiment remains the lead driver in the composite, 7D delta -4.3.
What can break
International expansion and AV initiatives add execution risk; management cited the UK expansion and future Nashville AV operations, while the 10-Q also flags competition from Waymo, Zoox, Baidu, Tesla, and other entrants. [#8-K-2026-05-07] [#10-Q-2026-05-08]
Momentum
19
Value
56
Sentiment
61
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $16.00 · Bull $20.00 · Bear $11.00
Data freshness
Prices
As of 2026-06-02
Fundamentals
As of 2026-06-01 • Vendor: Data Vendor v1
Scores
As of 2026-06-02 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-09 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-06-02
Supporting evidence
What
Grade D · Defensive
Confidence Medium · Net Neutral
Target $19.92
Why
Momentum19 · Δ7d +4.4
Value56 · Δ7d -0.5
Sentiment61 · Δ7d -4.3
So what
Weak posture (Net Neutral). Prioritize risk control and patience.
Lead driver: Sentiment · See AI snapshot
Momentum
19
34% active weight
Current posture
7d trendImproving
Δ7d
+4.4
Δ21d
+0.6
Value
56
32% active weight
Current posture
7d trendFlat
Δ7d
-0.5
Δ21d
-0.4
Sentiment
61
33% active weight
Current posture
7d trendSoftening
Δ7d
-4.3
Δ21d
+0.7
Why this grade

Composite grade D. Momentum 19.5 / Value 55.6 / Sentiment 61.2

Fundamentals (TTM)
As of 2026-06-01
Market Cap
$5.64B
Beta
1.94
Shares Out
407.88M
P/E (TTM)
53.9
P/S (TTM)
1.22
P/FCF (TTM)
7.44
Rev YoY
+10.7%
EPS YoY
+470.4%
Gross Margin
+35.2%
Op Margin
+0.4%
Net Debt
-$903.78M
Current Ratio
0.72
As of 2026-06-02 • Updated nightlySource: Internal modelMethodology