GENNEX (GENNEX) Fair Value & Analysis
IN · Market cap ₹2.5B
Fair value as of: Jul 5, 2026
From 14 valuation models · updated 3 days ago
Share price −8.3% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹7.13 – ₹17.02 · fair‑value band ₹11.01 – ₹18.35 · the ₹10.16 price screens below the ₹14.68 fair value. As of Jul 5, 2026.
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GENNEX (GENNEX) currently trades at ₹10.16, while our model-based Fair Value estimate is ₹14.68 — implying the stock looks roughly 44.5% undervalued today. We read business quality at 29/100 (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, GENNEX generated revenue of ₹1.7B at a net margin of 12.2%. Revenue grew 51.2% year over year. It earns a return on equity of 9.8%. Net debt stands at ₹793M. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹11.01 (bear case) to ₹18.35 (bull case); at ₹10.16, the current price sits below that range. The share trades about 41% below its 52-week high and 44% 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
FY2021 – FY2025 · reported fiscal years
GENNEX reported revenue of ₹1.7B in FY2025 versus ₹612M in FY2021, a compound +29.6%/yr. Reported net income was ₹210M in FY2025, compounding +52.1%/yr from FY2021.
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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.