Iwatani Corporation (IWTNF) Fair Value & Analysis
Industrials · US · Market cap $2.8B
Analysis
Iwatani Corporation (IWTNF) currently trades at $12.00, while our model-based Fair Value estimate is $21.96 — implying the stock looks roughly 83.0% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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
Iwatani Corporation engages in supplying gases and energy in Japan, China, Taiwan, South Korea, Singapore, Thailand, Malaysia, Indonesia, Vietnam, the United States, and Australia. It operates through four segments: Integrated Energy, Industrial Gases & Machinery, and Materials. The Integrated Energy segment offers LPG for household, commercial, and industrial use; LPG-supply equipment and facilities; LNG; petroleum products; household kitchen appliances; and home energy components, Ene farm, GHP, daily necessities, portable gas cooking stoves, cassette gas canisters, mineral water, health foods, and electricity. The Industrial Gases & Machinery segment provides air separation gases, hydrogen, helium, other specialty gases, gas supply facilities, welding materials, welding and cutting equipment, industrial robots, pumps and compressors, disaster prevention equipment, and high-pressure gas containers; and semiconductor manufacturing equipment, electronic component manufacturing equip…
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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.