Unifi, Inc (UFI) Fair Value & Analysis
Consumer Cyclical · US · Market cap $83.6M
Fair value as of: Jun 25, 2026
Analysis
Unifi, Inc (UFI) currently trades at $4.67, while our model-based Fair Value estimate is $5.16 — implying the stock looks roughly 10.5% undervalued today. We read business quality at 95/100 (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: low) — always confirm before acting.
About the company
Unifi, Inc., together with its subsidiaries, engages in the manufacture and sale of recycled and synthetic products in North America, Central America, South America, Asia, and Europe. It offers polyester products, including partially oriented yarn, textured, solution and package dyed, twisted, beamed, and draw wound yarns in virgin or recycled varieties; and nylon products comprise virgin or recycled textured, solution dyed, and spandex covered yarns. The company also provides recycled solutions made from pre-consumer and post-consumer waste, such as plastic bottle flakes, polyester polymer beads, and staple fiber. It offers recycled and synthetic products primarily to yarn manufacturers, knitters, and weavers that produces yarn and fabric for the apparel, hosiery, automotive, home furnishings, industrial, medical, and other end-use markets. The company sells its products through sales force and independent sales agents under the REPREVE brand. Unifi, Inc. was incorporated in 1969 a…
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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.