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TME

Tencent Music Entertainment GroupD
NYSE / Media & Entertainment
Last Price
At close
2026-07-20
View Chart
Current thesis
The primary company release supports a still-positive operating read: music-related services outgrew total revenue, margins improved, and cash increased despite a noisy IFRS earnings comparison. The strongest post-print bull interpretation is that subscription tiering, SVIP adoption, non-membership music revenue, and offline performance are offsetting weakness in social entertainment and can support a better mix if the trend persists.
Posture
Defensive
Lead driver
Value
What changed
Value remains the lead driver in the composite, 7D delta -0.8.
What can break
Fresh post-earnings analyst revision evidence remains limited at T+3, which keeps conviction low despite improved primary-source coverage.
Momentum
10
Value
62
Sentiment
43
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $9.10 · Bull $10.80 · Bear $7.20
Data freshness
Prices
As of 2026-07-20
Fundamentals
As of 2026-07-20 • Vendor: Data Vendor v1
Scores
As of 2026-07-20 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-15 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-07-20
Supporting evidence
What
Grade D · Defensive
Confidence Medium · Net Neutral
Target $14.31
Why
Momentum10 · Δ7d -0.4
Value62 · Δ7d -0.8
Sentiment43 · Δ7d -6.3
So what
Weak posture (Net Neutral). Prioritize risk control and patience.
Lead driver: Value · See fundamentals
Momentum
10
26% active weight
Current posture
7d trendFlat
Δ7d
-0.4
Δ21d
-0.3
Value
62
39% active weight
Current posture
7d trendFlat
Δ7d
-0.8
Δ21d
-1.5
Sentiment
43
34% active weight
Current posture
7d trendSoftening
Δ7d
-6.3
Δ21d
-10.1
Why this grade

Composite grade D. Momentum 9.7 / Value 61.8 / Sentiment 43.4

Fundamentals (TTM)
As of 2026-07-20
Market Cap
$13.11B
Beta
1.55
Shares Out
598.3M
P/E (TTM)
18.1
P/S (TTM)
6.16
P/FCF (TTM)
18.94
Rev YoY
+12.8%
EPS YoY
-49.2%
Gross Margin
+44.4%
Op Margin
+28.8%
Net Debt
-$2.94B
Current Ratio
2.09
As of 2026-07-20 • Updated nightlySource: Internal modelMethodology