LIXIL Corporation (JSGRY) Fair Value & Analysis
Industrials · US · Market cap $2.9B
Analysis
LIXIL Corporation (JSGRY) currently trades at $18.58, while our model-based Fair Value estimate is $9.92 — implying the stock looks roughly 46.6% overvalued today. We read business quality at 96/100 (high quality), in the Industrials 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: high).
About the company
LIXIL Corporation, through its subsidiaries, operates water technology and housing technology business in Japan and internationally. The company offers fixtures and vanities, which includes ceramic toilets, bidets, urinals, and basins, and vanities; bathing products, such as bath tubs, showers enclosures, whirlpool, and wellness solutions; and bathroom fittings, including single and two lever faucets and accessories, as well as hands and head showers, thermostats, and shower systems. It also provides shower toilets comprising integrated shower toilet system and seats; prefabricated bath and kitchen systems for houses condos, and other projects; smart water sensors and controllers; behind the wall systems and commercial fittings; kitchen fittings and sinks; and tiles. In addition, the company offers thermal efficiency and insulation windows; entrance doors; exteriors, including entrance gates, garages, terraces, and garden rooms; and wooden interior furnishing materials, as well as o…
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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.