HERCULES (HERCULES) Fair Value & Analysis
Industrials · Market cap ₹5.1B
Fair value as of: Jul 3, 2026
From 14 valuation models · updated today
Price vs Fair Value (12 months)
12‑month range ₹153.85 – ₹212.01 · fair‑value band ₹30.76 – ₹51.27 · the ₹159.32 price screens above the ₹41.02 fair value. As of Jul 3, 2026.
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HERCULES (HERCULES) currently trades at ₹159.32, while our model-based Fair Value estimate is ₹41.02 — implying the stock looks roughly 74.3% overvalued today. We read business quality at 56/100 (solid quality), in the Industrials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: medium).
Over the trailing twelve months, HERCULES generated revenue of ₹89.1M at a net margin of 86.7%. It earns a return on equity of 1.0%. The balance sheet holds a net cash position of ₹7.9M. The stock trades on a trailing P/E of 65.2. Fundamentals as of Jul 3, 2026
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 3, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
HERCULES reported revenue of ₹89.1M in FY2026 versus ₹1.1B in FY2022, a compound −46.4%/yr. Reported net income was ₹77.2M in FY2026, compounding −15.2%/yr from FY2022.
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Similar stocks
6 more Specialty Industrial Machinery stocks, each showing price versus our Fair Value estimate (as of Jul 3, 2026).
| Stock | Price | Fair Value | vs Fair Value |
|---|---|---|---|
| GE Vernova Inc GEV | $867.09 | $297.82 | -66% |
| SIEGY SIEGY | $155.06 | $89.54 | -42% |
| SMAWF SMAWF | $307.12 | $176.28 | -43% |
| SMNS SMNS | C$31.76 | C$22.91 | -28% |
| SIE SIE | €269.80 | €161.17 | -40% |
| Schneider Electric S.E. SBGSF | $334.00 | $148.44 | -56% |
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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.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.