NEAGI (NEAGI) Fair Value & Analysis
IN · Market cap ₹1.9B
Fair value as of: Jul 5, 2026
From 8 valuation models · updated today
Share price −7.6% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹3,036 – ₹3,789 · fair‑value band ₹4,403 – ₹7,656 · the ₹3,078 price screens below the ₹5,205 fair value. As of Jul 5, 2026.
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NEAGI (NEAGI) currently trades at ₹3,078, while our model-based Fair Value estimate is ₹5,205 — implying the stock looks roughly 69.1% undervalued today. We read business quality at 47/100 (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.
Trailing-twelve-month revenue stands at ₹254M. Revenue grew 53.3% year over year. It earns a return on equity of 9.3%. The stock trades on a trailing P/E of 6.6. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹4,403 (bear case) to ₹7,656 (bull case); at ₹3,078, the current price sits below that range. The share trades about 22% below its 52-week high and 3% 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
NEAGI reported revenue of ₹254M in FY2026 versus ₹296M in FY2022, a compound −3.7%/yr. Reported net income was ₹291M in FY2026, compounding −2.7%/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.