APAR Industries Limited (APARINDS) Fair Value & Analysis
Industrials · IN · Market cap ₹558B
Fair value as of: Jun 24, 2026
Analysis
APAR Industries Limited (APARINDS) currently trades at ₹16,654, while our model-based Fair Value estimate is ₹5,493 — implying the stock looks roughly 67.0% overvalued today. We read business quality at 97/100 (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
APAR Industries Limited engages in the electrical and metallurgical engineering business in India and internationally. It operates through Conductor, Transformer & Specialties Oils, Power/Telecom Cables, and Others segments. The company offers transformer oils, including naphthenic and iso--paraffinic grades; liquid paraffins that are used in baby oil, medical and pharma, cosmetic, food packaging and coating, personal care, bakery, and plastic industries; petroleum jelly for use in personal care, pharmaceutical formulations, dermatological and ophthalmic formulations, battery terminal compounds, release agents for plaster molds and castings, and leather industries; process oils for rubber and tires, EPDM rubber/profiles, low PCA oils, TPE and plastics, hot melt adhesives, ink oils, and base oils for metal working fluids; and process oils for general applications. It also provides CTC/PICC conductors, railway overhead conductors, T&D overhead conductors, optical ground wires, aluminu…
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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.