RACE

FerrariC

NYSE / Automobiles & Components

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Current thesis

Composite grade C from latest DB weights. Momentum 75.8 / Value 49.5

Posture

Mixed

Lead driver

Value

What changed

Value remains the lead driver in the composite, 7D delta -0.2.

What can break

Mixed signals. Wait for cleaner trend confirmation.

Momentum

Value

Sentiment

N/A

Setup hits (3d)

0 · Net Neutral

AI TargetsBase - · Bull - · Bear -Analysis date unavailable; returns require an exact persisted reference.

Data freshness

Prices

Unavailable: Price unavailable

Fundamentals

As of 2026-10-23 • Vendor: Data Vendor v1

Scores

As of 2026-10-23 • Model: HYBRID_IC_RP

AI Memo

Unavailable: No memo yet

Investment thesis

As of 2026-10-23

Grade is the composite factor band; factor scores use a 0–100 scale. Confidence describes evidence quality, not a probability of return. Score date: 2026-10-23. Definitions

Supporting evidence

What

Grade C · Mixed

Confidence Medium · Net Neutral

Target $456.72

Why

Momentum76 · Δ7d -28.1

Value49 · Δ7d -0.2

SentimentN/A · Δ7d -

So what

Balanced signals (Net Neutral). Wait for confirmation before sizing up.

Confirming evidence

• Value remains the lead driver in the composite, 7D delta -0.2.

Contradictions & invalidation

• Mixed signals. Wait for cleaner trend confirmation.

Catalyst clock

No dated catalyst is available.

Lead driver: Value · See fundamentals

Momentum

15% active weight

Current posture

7d trendSoftening

Δ7d

-28.1

Δ21d

-25.8

Value

85% active weight

Current posture

7d trendFlat

Δ7d

-0.2

Δ21d

-0.6

Sentiment

N/A

Coverage pending

No current score

7d trendTrend unavailable

Trend unavailable

Δ7d

Δ21d

Why this grade

Composite grade C. Momentum 75.8 / Value 49.5

Fundamentals (TTM)

As of 2026-10-23

Market Cap

$86.39B

Beta

0.75

Shares Out

159.27M

P/E (TTM)

35.9

P/S (TTM)

8.80

P/FCF (TTM)

47.17

Rev YoY

+11.2%

EPS YoY

+13.0%

Gross Margin

+51.9%

Op Margin

+29.8%

Net Debt

$1.57B

Current Ratio

2.37

As of 2026-10-23 • Updated nightlySource: Internal modelMethods & Data