Arlo Technologies, Inc (ARLO) Fair Value & Analysis
Industrials · US · Market cap $1.4B
Analysis
Arlo Technologies, Inc (ARLO) currently trades at $12.81, while our model-based Fair Value estimate is $2.48 — implying the stock looks roughly 80.6% overvalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Arlo Technologies, Inc., together with its subsidiaries, provides cloud-based platform services in the Americas, Europe, the Middle East, Africa, and the Asia Pacific regions. The company offers Arlo Essential Cameras and Doorbells delivers smart home protection, including automated privacy shield, 360-degree coverage, and 2K video resolution; Arlo Home Security System, an all-in-one multi-sensor that provides access to security experts for monitoring and responding to emergency situations; ARLO PRO 6, a pro series wireless security cameras; ARLO ULTRA 3, a 4K HDR video resolution, auto-zoom and tracking and an expansive 180-degree field of view camera; Arlo Go 2, a camera for monitoring remote areas, large properties, construction sites, vacation homes, boat or RV slips, and hard-to-access areas; and Arlo Floodlight Camera, a wire-free floodlight camera. It also provides security system accessories, charging accessories, and mounts. In addition, the company offers Arlo Secure subsc…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.