SHIVA (SHIVA) Fair Value & Analysis
IN · Market cap ₹60.9M
Fair value as of: Jul 6, 2026
From 20 valuation models · updated today
Share price +5.9% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹6.19 – ₹12.21 · fair‑value band ₹7.95 – ₹13.93 · the ₹9.76 price screens below the ₹10.61 fair value. As of Jul 6, 2026.
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SHIVA (SHIVA) currently trades at ₹9.76, while our model-based Fair Value estimate is ₹10.61 — implying the stock looks roughly 8.7% undervalued today. We read business quality at 70/100 (solid 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: high) — always confirm before acting.
Over the trailing twelve months, SHIVA generated revenue of ₹26.5M at a net margin of 16.1%. Revenue grew 91.7% year over year. It earns a return on equity of 6.4%. Net debt stands at ₹23.8M. Fundamentals as of Jul 6, 2026
Our scenario range runs from ₹7.95 (bear case) to ₹13.93 (bull case); at ₹9.76, the current price sits within that range. The share trades about 27% below its 52-week high and 69% above its 52-week low, currently above its 200-day average.
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 6, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2021 – FY2025 · reported fiscal years
SHIVA reported revenue of ₹26.5M in FY2025 versus ₹4.8B in FY2021, a compound −72.7%/yr. Reported net income was ₹4.3M in FY2025, compounding −61.8%/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.