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Nutrition Profess Public Company (NUT) Fair Value & Analysis

Consumer Defensive · TH · Market cap 506M THB

Price4.92 THB
Fair Value9.70 THB
Upside+97.2%
Quality87/100
Evidence: Medium Range 7.28 THB – 12.13 THB

Fair value as of: Jun 25, 2026

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Analysis

Nutrition Profess Public Company (NUT) currently trades at 4.92 THB, while our model-based Fair Value estimate is 9.70 THB — implying the stock looks roughly 97.2% undervalued today. We read business quality at 87/100 (high quality), in the Consumer Defensive sector. 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.

About the company

Nutrition Profess Public Company Limited manufactures, trades, and distributes pharmaceutical products, food supplements, chemicals, cosmetics, and cosmeceuticals through online and offline channels. It also provides OEM / ODM contract manufacturing services; design services; and consulting services. Nutrition Profess Public Company Limited was founded in 2013 and is based in Bangkok, Thailand.

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Frequently asked questions

Is Nutrition Profess Public Company (NUT) undervalued?
As of Jun 25, 2026, our model estimates a fair value of 9.70 THB versus a price of 4.92 THB — about +97% (undervalued). Model-based estimate, not financial advice.
What is the fair value of NUT?
Our 21-model fair value for Nutrition Profess Public Company is 9.70 THB (as of Jun 25, 2026), built from audited fundamentals. The current price is 4.92 THB.
What is the quality score of NUT?
Nutrition Profess Public Company has a Quality Score of 87/100, 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.