CCLINTER (CCLINTER) Fair Value & Analysis
IN · Market cap ₹457M
Fair value as of: Jul 5, 2026
From 21 valuation models · updated today
Share price −2.7% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹20.50 – ₹32.79 · fair‑value band ₹7.89 – ₹11.26 · the ₹23.80 price screens above the ₹11.26 fair value. As of Jul 5, 2026.
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CCLINTER (CCLINTER) currently trades at ₹23.80, while our model-based Fair Value estimate is ₹11.26 — implying the stock looks roughly 52.7% overvalued today. We read business quality at 50/100 (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, CCLINTER generated revenue of ₹504M at a net margin of 1.9%. Revenue declined 6.1% year over year. It earns a return on equity of 2.0%. Net debt stands at ₹190M. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹7.89 (bear case) to ₹11.26 (bull case); at ₹23.80, the current price sits above that range. The share trades about 33% below its 52-week high and 19% 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
CCLINTER reported revenue of ₹504M in FY2026 versus ₹268M in FY2022, a compound +17.1%/yr. Reported net income was ₹9.5M in FY2026, compounding +13.6%/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.