BRANDBUCKT (BRANDBUCKT) Fair Value & Analysis
IN · Market cap ₹114M
Fair value as of: Jul 5, 2026
From 14 valuation models · updated today
Price vs Fair Value (12 months)
12‑month range ₹4.90 – ₹4.90 · fair‑value band ₹5.47 – ₹9.11 · the ₹4.90 price screens below the ₹7.29 fair value. As of Jul 5, 2026.
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BRANDBUCKT (BRANDBUCKT) currently trades at ₹4.90, while our model-based Fair Value estimate is ₹7.29 — implying the stock looks roughly 48.8% undervalued today. We read business quality at 42/100 (below-average 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: medium) — always confirm before acting.
Over the trailing twelve months, BRANDBUCKT generated revenue of ₹438M at a net margin of 1.6%. Revenue grew 106.6% year over year. It earns a return on equity of 1.8%. The stock trades on a trailing P/E of 17.5. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹5.47 (bear case) to ₹9.11 (bull case); at ₹4.90, the current price sits below that range. The share trades near its 52-week high, 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
FY2021 – FY2024 · reported fiscal years
BRANDBUCKT reported revenue of ₹342M in FY2024 versus ₹152M in FY2021, a compound +31.1%/yr. Reported net income was ₹8.5M in FY2024, compounding +42.7%/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.