Dynemic Products Limited (DYNPRO) Fair Value & Analysis
Basic Materials · IN · Market cap ₹2.9B
Fair value as of: Jun 29, 2026
Analysis
Dynemic Products Limited (DYNPRO) currently trades at ₹235.20, while our model-based Fair Value estimate is ₹272.79 — implying the stock looks roughly 16.0% undervalued today. We read business quality at 97/100 (high quality), in the Basic Materials 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: high) — always confirm before acting.
About the company
Dynemic Products Limited, together with its subsidiaries, engages in the manufacture and sale of dyes and dye intermediates in India. It offers synthetic food colours that are primarily applied in colouring food, drug, and cosmetic products; lake colours for use in pharmaceuticals, cosmetic and personal care products, spice compounds, bakery and dairy products, and snack food applications; and blended colours. The company also provides food drug and cosmetic colors; salt free dyes for the inkjet industry; and dyes intermediates, such as pyarazolone based dyes intermediates. In addition, it offers drug and cosmetic colours for tablet coatings, compressed tablets, syrups, hard and soft gelatin capsules, toiletries, skin-care products, water-based make-ups, lipsticks, nail polishes, pencils, foundations, and lip glosses; and natural food colours. The company also exports its products. Dynemic Products Limited was incorporated in 1990 and is based in Ahmedabad, India.
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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.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.