Nichicon Corporation (NCHNF) Fair Value & Analysis
Technology · US · Market cap $495M
Analysis
Nichicon Corporation (NCHNF) currently trades at $7.37, while our model-based Fair Value estimate is $12.37 — implying the stock looks roughly 67.8% undervalued today. We read business quality at 95/100 (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
Nichicon Corporation, together with its subsidiaries, engages in the development and production of electrical components in Japan, the United States, Asia, Europe, and internationally. It offers chip aluminum electrolytic capacitors; conductive polymer aluminum solid electrolytic capacitors; conductive polymer hybrid aluminum solid electrolytic capacitors; large can aluminum electrolytic capacitors; and miniature aluminum electrolytic capacitors. The company also provides film capacitors for xEV; lithium titanate rechargeable batteries for use in space-constrained IoT applications; energy control system technology; switching power supplies; capacitors for power utilities; special power supplies; function modules; and Posi-R thermistors. Its products are used in automotive, power supply and lighting, information and communications, industrial, DC link capacitors, asset tracking, energy harvesting, internet of things, wireless sensors, RFID, smart pallet, and pick to light application…
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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.