Ashnoor Textile Mills Limited (507872) Fair Value & Analysis
Other · IN · Market cap ₹128M
Fair value as of: Jul 4, 2026
From 22 valuation models · updated today
Share price +0.6% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹35.20 – ₹53.68 · fair‑value band ₹5.28 – ₹8.80 · the ₹38.72 price screens above the ₹7.04 fair value. As of Jul 4, 2026.
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Ashnoor Textile Mills Limited (507872) currently trades at ₹38.72, while our model-based Fair Value estimate is ₹7.04 — implying the stock looks roughly 81.8% overvalued today. We read business quality at 50/100 (solid quality), in the Other 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).
Over the trailing twelve months, Ashnoor Textile Mills Limited generated revenue of ₹995M at a net margin of 2.4%. Revenue declined 46.5% year over year. It earns a return on equity of 6.5%. Net debt stands at ₹544M. Fundamentals as of Jul 4, 2026
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 4, 2026. TTM = trailing twelve months.
About the company
Ashnoor Textile Mills Limited produces and sells terry towels primarily in India. The company offers white, colored, pool dobby, and kitchen towels to hospitality industry. It operates through a network of retailers and distributors. The company also exports its products to the United States. Ashnoor Textile Mills Limited was incorporated in 1984 and is based in Gurugram, India.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
Ashnoor Textile Mills Limited reported revenue of ₹1.1B in FY2026 versus ₹2.6B in FY2022, a compound −18.8%/yr. Reported net income was ₹84.8M in FY2026, compounding −1.3%/yr from FY2022.
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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.