Dynamatic Technologies Limited (DYNAMATECH) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹69.2B
Fair value as of: Jun 29, 2026
Analysis
Dynamatic Technologies Limited (DYNAMATECH) currently trades at ₹10,232, while our model-based Fair Value estimate is ₹1,050 — implying the stock looks roughly 89.7% overvalued today. We read business quality at 97/100 (high quality), in the Consumer Cyclical 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
Dynamatic Technologies Limited manufactures and sells engineered products to the aerospace, automotive, and hydraulic industries in India, the United States, the United Kingdom, rest of Europe, Canada, and internationally. The company offers gear pumps, low noise pumps, high-pressure pumps, axial piston pumps, low torque high-speed hydraulic motors, plunger hand pumps, hitch control valves, rock shaft assemblies, power steering valves, and mobile control valves; and bespoke, high-flow scavenging pumps, lube oil pumps, and water pumps. It also provides high-precision airframe and aerospace components; control surfaces, such as wings, ailerons, wing flaps, fuselages, and doors; key flight-critical airframe structures, such as flap track beams; and intricate iron castings. In addition, the company offers geared motors; power steering units; construction equipment; and aluminium body, hydraulic gear pumps and motors from low to very high-pressure ratings, integrated gear and piston pump…
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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.