Stoneridge, Inc (SRI) Fair Value & Analysis
Consumer Cyclical · US · Market cap $204M
Fair value as of: Jun 24, 2026
Analysis
Stoneridge, Inc (SRI) currently trades at $6.87, while our model-based Fair Value estimate is $4.27 — implying the stock looks roughly 37.8% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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: medium).
About the company
Stoneridge, Inc., together with its subsidiaries, designs, manufactures, and sells engineered electrical and electronic systems, components, and modules for the commercial, automotive, off-highway, and agricultural vehicle markets in North America, South America, Europe, and the Asia Pacific. The company operates in two segments, Electronics and Stoneridge Brazil. The Electronics segment offers advanced driver information solutions, vision systems, connectivity and compliance solutions, and control modules for commercial vehicle and off-highway markets through OEM and aftermarket channels. The Stoneridge Brazil segment provides vehicle tracking devices and monitoring services, driver information systems, vehicle security alarms and convenience accessories, and telematics solutions and multimedia devices primarily for the automotive and commercial vehicle markets through aftermarket distribution channel, direct to OEMs, and factory authorized dealer installers. It sells monitoring se…
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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.