Shibusawa Logistics Corporation (SWRHF) Fair Value & Analysis
Industrials · US · Market cap $264M
Fair value as of: Jun 25, 2026
Analysis
Shibusawa Logistics Corporation (SWRHF) currently trades at $4.57, while our model-based Fair Value estimate is $8.94 — implying the stock looks roughly 95.8% 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: medium) — always confirm before acting.
About the company
Shibusawa Logistics Corporation provides logistics and warehousing services in Japan and internationally. The company provides strategic logistics services, such as warehousing and distribution processing for various types of cargo; truck transportation services, including consolidated transportation, chartered transportation, and ocean freight container transportation for customer's logistics; ocean and air import and export handling services comprising customs clearance, overland transport, and warehouse storage at departure and arrival ports and airports; document storage and trunk room storage; and moving &household goods storage. It is also involved in EC fulfillment services; customs clearance; trade/intermediary business/management/leading of real estate; packaging/indication/storage of pharmaceuticals/quasi-drugs/cosmetics and medical equipment; planning/development/sales/operation management of information systems; employment agency; and life support of non-covered long-ter…
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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.