Dunelm Group (DNLM) Fair Value & Analysis
Consumer Cyclical · GB · Market cap 1.5B GBX
Analysis
Dunelm Group (DNLM) currently trades at p7.86, while our model-based Fair Value estimate is p16.43 — implying the stock looks roughly 109.2% 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: high) — always confirm before acting.
About the company
Dunelm Group plc engages in the retail of homewares in the United Kingdom. The company offers furniture and beds products, which include bedroom, living room, dining room, and other furniture, as well as bed and mattresses, and sofas and armchairs; bedding products comprising bed linen, dorma, baby and kid's bedding, duvets, pillows, and protectors; curtains; rugs; and venetian, roller, roman, vertical, and made to measure blinds. It also offers range of home decor products, such as wall art and décor, mirrors, clocks, ornaments, pictures and frames, candle and home fragrance, flower and plants, vases, decorative trays and bowls, kid's decor, coffee table books, plant pots, cushions, throws, draught excluders, fireplace extras, and bean bags, as well as housewarming, engagement, personalised, anniversary, wedding gifts, and gift cards; and lighting products, including ceiling lights, lamp shades, table lamps, floor lamps, wall lights, chandeliers, led lighting, bathroom lighting, ou…
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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.