ORGANICREC (ORGANICREC) Fair Value & Analysis
IN · Market cap ₹2.4B
Fair value as of: Jul 5, 2026
From 14 valuation models · updated today
Share price −1.8% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹214.65 – ₹345.25 · fair‑value band ₹266.38 – ₹443.97 · the ₹231.30 price screens below the ₹355.17 fair value. As of Jul 5, 2026.
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ORGANICREC (ORGANICREC) currently trades at ₹231.30, while our model-based Fair Value estimate is ₹355.17 — implying the stock looks roughly 53.6% undervalued today. We read business quality at 48/100 (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: medium) — always confirm before acting.
Over the trailing twelve months, ORGANICREC generated revenue of ₹1.1B at a net margin of 23.9%. Revenue grew 186.9% year over year. It earns a return on equity of 19.4%. Net debt stands at ₹420M. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹266.38 (bear case) to ₹443.97 (bull case); at ₹231.30, the current price sits below that range. The share trades about 39% below its 52-week high and 12% 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
ORGANICREC reported revenue of ₹1.1B in FY2026 versus ₹146M in FY2022, a compound +63.9%/yr. Reported net income was ₹251M in FY2026.
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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.