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Dreamfolks Services Limited (DREAMFOLKS) Fair Value & Analysis

Industrials · IN · Market cap ₹3.6B

Price₹67.54
Fair Value₹44.13
Upside-34.7%
Quality94/100
Evidence: High Range ₹43.05 – ₹48.96

Fair value as of: Jun 29, 2026

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Analysis

Dreamfolks Services Limited (DREAMFOLKS) currently trades at ₹67.54, while our model-based Fair Value estimate is ₹44.13 — implying the stock looks roughly 34.7% overvalued today. We read business quality at 94/100 (high quality), in the Industrials 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).

About the company

Dreamfolks Services Limited provides airport service in India. The company provides lounge access, meet and assist, airport transfers, food and beverages, door-step baggage, and spa and wellness services. Dreamfolks Services Limited was incorporated in 2008 and is based in Gurugram, India.

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Frequently asked questions

Is Dreamfolks Services Limited (DREAMFOLKS) undervalued?
As of Jun 29, 2026, our model estimates a fair value of ₹44.13 versus a price of ₹67.54 — about −35% (overvalued). Model-based estimate, not financial advice.
What is the fair value of DREAMFOLKS?
Our 21-model fair value for Dreamfolks Services Limited is ₹44.13 (as of Jun 29, 2026), built from audited fundamentals. The current price is ₹67.54.
What is the quality score of DREAMFOLKS?
Dreamfolks Services Limited has a Quality Score of 94/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.