Fairvalue-Calculator Fairvalue-Calculator

TACHI-S Co (TCISF) Fair Value & Analysis

Consumer Cyclical · US · Market cap $526M

Price$15.34
Fair Value$33.22
Upside+116.6%
Quality96/100
Evidence: High Range $25.45 – $42.10

Analysis

TACHI-S Co (TCISF) currently trades at $15.34, while our model-based Fair Value estimate is $33.22 — implying the stock looks roughly 116.6% undervalued today. We read business quality at 96/100 (high quality), in the Consumer Cyclical 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

TACHI-S Co., Ltd., together with its subsidiaries, manufactures and sells automotive seats and seat parts in Japan, the United States, Mexico, rest of North America, Central and South America, Southeast Asia, China, Europe, and internationally. The company offers seats for various cars, such as luxury brand cars, sports cars, mini cars, and commercial vehicles. It also provides mechanical parts comprising seat tracks, height adjusters, round recliners, side frames, and latches; trim covers, such as seat, armrest, and headrest covers; parts and medical-related products; and special vehicles. The company was formerly known as Tachikawa Spring Co., Ltd. and changed its name to TACHI-S Co., Ltd. in April 1986. TACHI-S Co., Ltd. was incorporated in 1954 and is headquartered in Ome, Japan.

Open the full interactive analysis →

Similar stocks

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.