NOL (NOL) Fair Value & Analysis
IN · Market cap ₹276M
Fair value as of: Jul 5, 2026
From 6 valuation models · updated today
Share price −23.3% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹47.62 – ₹144.25 · fair‑value band ₹54.63 – ₹91.06 · the ₹54.75 price screens below the ₹72.85 fair value. As of Jul 5, 2026.
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NOL (NOL) currently trades at ₹54.75, while our model-based Fair Value estimate is ₹72.85 — implying the stock looks roughly 33.1% undervalued today. We read business quality at 33/100 (below-average quality). 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: low) — always confirm before acting.
Over the trailing twelve months, NOL generated revenue of ₹230M at a net margin of 8.0%. Revenue declined 54.0% year over year. Net debt stands at ₹281M. The stock trades on a trailing P/E of 15.0. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹54.63 (bear case) to ₹91.06 (bull case); at ₹54.75, the current price sits within that range. The share trades about 63% below its 52-week high and 29% above its 52-week low, currently below its 200-day average.
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 5, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
NOL reported revenue of ₹230M in FY2026 versus ₹506M in FY2022, a compound −17.9%/yr. Reported net income was ₹18.4M in FY2026, compounding −29.9%/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.
Not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.