MMRUBBR-B Fair Value & Analysis
IN · Market cap ₹363M
Fair value as of: Jul 8, 2026
From 10 valuation models · updated 13 days ago
Share price −3.6% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹55.06 – ₹101.46 · fair‑value band ₹4.49 – ₹21.71 · the ₹60.75 price screens above the ₹13.10 fair value. As of Jul 8, 2026.
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MMRUBBR-B (MMRUBBR-B) currently trades at ₹60.75, while our model-based Fair Value estimate is ₹13.10, implying the stock looks roughly 78.4% overvalued today. We read business quality at 47/100 (below-average 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: medium).
Over the trailing twelve months, MMRUBBR-B generated revenue of ₹401M at a net margin of -3.0%. Revenue grew 5.3% year over year. It earns a return on equity of -9.0%. Net debt stands at ₹97.2M. Fundamentals as of Jul 8, 2026
Our scenario range runs from ₹4.49 (bear case) to ₹21.71 (bull case); at ₹60.75, the current price sits above that range. The share trades about 42% below its 52-week high and 13% 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 8, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
MMRUBBR-B reported revenue of ₹401M in FY2026 versus ₹372M in FY2022, a compound +1.9%/yr. Reported net income was −₹12.0M in FY2026.
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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.
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Not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.