GRND

GrindrA

NYSE / Media & Entertainment

At close

2026-07-21

Current thesis

The post-earnings read is constructive: Q1 growth was strong across app-based revenue and advertising, paying users rose to 1.385M, ARPPU increased to $25.63, and management raised 2026 guidance while still funding product, AI, and platform expansion.

Posture

Constructive

Lead driver

Momentum

What changed

Momentum remains the lead driver in the composite, 7D delta -0.7.

What can break

As of March 31, 2026, cash and cash equivalents were $23.8M against total debt of $391.1M after aggressive repurchase activity, leaving the capital-return story more dependent on continued operating cash generation and revolver flexibility [#10-Q-2026-05-08].

Momentum

Value

Sentiment

Setup hits (3d)

0 · Net Neutral

AI TargetsBase $15.50 · Bull $18.00 · Bear $11.50

Data freshness

Prices

As of 2026-07-21

Fundamentals

As of 2026-07-20 • Vendor: Data Vendor v1

Scores

As of 2026-07-21 • Model: HYBRID_IC_RP

AI Memo

As of 2026-05-08 • Model: RankAlpha Sentiment Codex

Investment thesis

As of 2026-07-21

Supporting evidence

What

Grade A · Constructive

Confidence Medium · Net Neutral

Target $18.80

Why

Momentum93 · Δ7d -0.7

Value54 · Δ7d +0.2

Sentiment48 · Δ7d -2.4

So what

Strength-led posture (Net Neutral). Favor watchlist adds and disciplined entries.

Lead driver: Momentum · See technicals

Momentum

26% active weight

Current posture

7d trendSoftening

Δ7d

-0.7

Δ21d

+53.9

Value

39% active weight

Current posture

7d trendFlat

Δ7d

+0.2

Δ21d

-0.4

Sentiment

34% active weight

Current posture

7d trendSoftening

Δ7d

-2.4

Δ21d

-11.4

Why this grade

Composite grade A. Momentum 92.8 / Value 53.6 / Sentiment 48.2

Fundamentals (TTM)

As of 2026-07-20

Market Cap

$2.77B

Beta

0.23

Shares Out

177.73M

P/E (TTM) · Derived

31.2

P/S (TTM)

5.96

P/FCF (TTM)

17.60

Rev YoY

+38.3%

EPS YoY

+69.8%

Gross Margin

+73.3%

Op Margin

+28.0%

Net Debt

$313.54M

Current Ratio

1.26

As of 2026-07-21 • Updated nightlySource: Internal modelMethodology