FRONTSP (FRONTSP) Fair Value & Analysis
IN · Market cap ₹17.2B
Fair value as of: Jul 5, 2026
From 24 valuation models · updated today
Share price −3.6% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹1,227 – ₹1,795 · fair‑value band ₹663.01 – ₹2,392 · the ₹1,455 price screens above the ₹943.42 fair value. As of Jul 5, 2026.
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FRONTSP (FRONTSP) currently trades at ₹1,455, while our model-based Fair Value estimate is ₹943.42 — implying the stock looks roughly 35.2% overvalued today. We read business quality at 61/100 (solid quality). 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, FRONTSP generated revenue of ₹3.2B at a net margin of 19.0%. Revenue grew 17.8% year over year. It earns a return on equity of 39.9%. Net debt stands at ₹73.0M. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹663.01 (bear case) to ₹2,392 (bull case); at ₹1,455, the current price sits within that range. The share trades about 22% below its 52-week high and 24% 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 5, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
FRONTSP reported revenue of ₹3.2B in FY2026 versus ₹836M in FY2022, a compound +40.1%/yr. Reported net income was ₹613M in FY2026, compounding +69.0%/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.