Big Yellow Group (BYG) Fair Value & Analysis
Real Estate · GB · Market cap 1.6B GBX
Fair value as of: Jun 26, 2026
Analysis
Big Yellow Group (BYG) currently trades at p9.20, while our model-based Fair Value estimate is p9.01 — implying the stock looks roughly 2.1% overvalued today. We read business quality at 97/100 (high quality), in the Real Estate 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
Big Yellow Group Plc is the UK's brand leader in self-storage and operates from a platform of 111 stores. We have a pipeline of 0.9 million sq ft comprising 13 proposed self-storage facilities. The current maximum lettable area of the existing platform is 6.6 million sq ft. When fully built out the portfolio will provide approximately 7.5 million sq ft of flexible storage space. 99% of our stores and sites by value are held freehold and long leasehold, with the remaining 1% short leasehold. Currently by revenue 75% of our stores are in London and its commuter towns, with the balance in larger regional conurbations. Our stores utilize state of the art technology for our digital and operating platforms including security, and we focus on locating our stores in high profile, accessible, main road locations. We also focus on providing excellent customer service, a highly engaged employee culture, and with a significant investment in sustainability. Big Yellow Group Plc was incorporated …
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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.