Archies Limited (ARCHIES) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹485M
Fair value as of: Jun 29, 2026
Analysis
Archies Limited (ARCHIES) currently trades at ₹14.29, while our model-based Fair Value estimate is ₹1.60 — implying the stock looks roughly 88.8% 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
Archies Limited engages in the retail sale of cultural, recreation, and other goods in India and internationally. It operates through Greeting Cards; Stationery and Paper Bag Items; Gifts; and Others segments. The company offers birthday products; jewellery and accessories comprising necklaces, earrings, tote bags, bracelets, keychains, watches, wallets, and bags; greeting cards; gift products consisting of mugs, showpieces, soft toys, divine idols and gifts, photo albums and frames, handing, clocks, candles, water bottles and flasks, trophies, pen stands, wind chimes, quotations, glassware and bar accessories, artificial flowers, and card cases, as well as chocolates; and same day delivery and personalized gift products. It also provides stationery products comprising notebooks, diaries, quotation books, collectibles, scrap books, shagun envelopes, calendars, paper bags, and scrolls; beauty and personal care products, such as deodorant, perfume, fragrance gift set, and skincare pro…
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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.