ams-OSRAM AG (AMS2) Fair Value & Analysis
Technology · AT · Market cap €2.2B
Analysis
ams-OSRAM AG (AMS2) currently trades at €20.10, while our model-based Fair Value estimate is €28.39 — implying the stock looks roughly 41.2% undervalued today. We read business quality at 91/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
ams-OSRAM AG engages in the design, manufacture, and sale of LED and optical sensor solutions in Europe, the Middle East, Africa, the United States, and the Asia/Pacific. The company operates through Opto Semiconductors (OS); CMOS Sensors & ASICs (CSA); and Lamps & Systems (L&S) segments. It offers white, color, UV-C, IR, and multi color LEDs, as well as LED modules and accessories; color and IR lasers; photodiodes and phototransistors; optical modules; and automotive and digital systems and lamps, as well as power management ICs, LED driver and analog frontend ICs, and sensor interfaces. In addition, the company provides ambient light, color, and spectral and proximity sensors; direct time-of-flight sensors; position and capacitive sensors; CMOS image sensors; temperature sensors; active noise cancellation solutions; and boards, kits, and related accessories. Its products are used in automotive and mobility, industrial, medical and health, mobile and wearables, lighting, and comput…
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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.