Barnes & Noble Education, Inc (BNED) Fair Value & Analysis
Consumer Cyclical · US · Market cap $363M
Fair value as of: Jun 24, 2026
Analysis
Barnes & Noble Education, Inc (BNED) currently trades at $10.70, while our model-based Fair Value estimate is $5.32 — implying the stock looks roughly 50.3% overvalued today. We read business quality at 97/100 (high quality), in the Consumer Cyclical 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: medium).
About the company
Barnes & Noble Education, Inc. operates bookstores for college and university campuses, and K-12 institutions primarily in the United States. The company sells and rents new and used print textbooks, digital textbooks, and publisher hosted digital courseware through physical and virtual bookstores, as well as directly to students through Textbooks.com. In addition, it offers First Day and First Day Complete access programs; and general merchandise, including collegiate and athletic apparel, school spirit products, lifestyle and wellness products, technology products, supplies, graduation products, and convenience items. Further, the company sources, sells, and distributes new and used textbooks; and sells hardware and a software suite of applications that provides inventory management and point-of-sale solutions to college bookstores. Additionally, it offers direct-to-student services. It operates physical college and university bookstores; virtual bookstores; True Spirit e apparel …
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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.