HAPPSTMNDS (HAPPSTMNDS) Fair Value & Analysis
Technology · Market cap ₹53.2B
Fair value as of: Jul 3, 2026
From 26 valuation models · updated today
Share price −7.0% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹336.90 – ₹640.23 · fair‑value band ₹212.25 – ₹353.75 · the ₹351.95 price screens above the ₹283.00 fair value. As of Jul 3, 2026.
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HAPPSTMNDS (HAPPSTMNDS) currently trades at ₹351.95, while our model-based Fair Value estimate is ₹283.00 — implying the stock looks roughly 19.6% overvalued today. We read business quality at 47/100 (below-average quality), in the Technology 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: high).
Over the trailing twelve months, HAPPSTMNDS generated revenue of ₹23.2B at a net margin of 9.2%. Revenue grew 10.9% year over year. It earns a return on equity of 13.0%. Net debt stands at ₹5.7B. 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
HAPPSTMNDS reported revenue of ₹23.2B in FY2026 versus ₹10.9B in FY2022, a compound +20.6%/yr. Reported net income was ₹2.1B in FY2026, compounding +4.1%/yr from FY2022.
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Similar stocks
6 more Information Technology Services stocks, each showing price versus our Fair Value estimate (as of Jul 3, 2026).
| Stock | Price | Fair Value | vs Fair Value |
|---|---|---|---|
| International Business Machines Corporation IBM | $301.77 | $153.91 | -49% |
| Accenture plc ACN | $129.15 | $250.14 | +94% |
| Tata Consultancy Services Limited TCS | ₹2,154 | ₹2,580 | +20% |
| Infosys Limited INFY | ₹1,198 | ₹1,237 | +3% |
| HCL Technologies Limited HCLTECH | ₹1,131 | ₹2,568 | +127% |
| Fiserv, Inc FISV | 930.00 MXN | 109.65 MXN | -88% |
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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.