Wilhelmina International, Inc (WHLM) Fair Value & Analysis
Industrials · US · Market cap $13.5M
Fair value as of: Jun 25, 2026
Analysis
Wilhelmina International, Inc (WHLM) currently trades at $2.75, while our model-based Fair Value estimate is $3.59 — implying the stock looks roughly 30.5% undervalued today. We read business quality at 92/100 (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
Wilhelmina International, Inc. primarily engages in the fashion model management business. It specializes in the representation and management of models, entertainers, athletes, and other talent to various clients, including retailers, designers, advertising agencies, print and electronic media and catalog companies. The company also provides fashion modeling talent and social media influencer services to clients, such as advertising agencies, branded consumer goods companies, fashion designers, Internet sites, retailers, department stores, product catalogs, and magazine publications. In addition, the company is involved in the licensing of the Wilhelmina name to third parties, such as fashion model agencies; television syndication royalties and production series contracts; and model search contests. It has operations in Los Angeles, Miami, and London, as well as a network of licensees in various local markets in the United States and internationally. Wilhelmina International, Inc. …
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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.