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Gujarat Fluorochemicals Limited (FLUOROCHEM) Fair Value & Analysis

Basic Materials · IN · Market cap ₹391B

Price₹3,891
Fair Value₹836.47
Upside-78.5%
Quality96/100
Evidence: High Range ₹592.41 – ₹1,087

Analysis

Gujarat Fluorochemicals Limited (FLUOROCHEM) currently trades at ₹3,891, while our model-based Fair Value estimate is ₹836.47 — implying the stock looks roughly 78.5% overvalued today. We read business quality at 96/100 (high quality), in the Basic Materials 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

Gujarat Fluorochemicals Limited engages in the manufacture and trading of refrigerant gases, fluorochemicals, fluoropolymers, battery chemicals, wind energy, and renewable energy solutions in India, Europe, the United States, and internationally. It provides caustic soda, carbon tetrachloride, chlorine, methylene di chloride, hydrochloric acid, sodium hydrogen sulphate, hydrogen gas, fluorspar, chloroform, and anhydrous hydrogen chloride. The company offers its products under the INOFLON, FLUONOX, INOFLAR, INOLUB, and Refron brands. It provides its products to agrochemicals, pharmaceuticals, battery materials, and other sectors. The company was formerly known as Inox Fluorochemicals Limited and changed its name to Gujarat Fluorochemicals Limited in July 2019. The company was incorporated in 1987 and is headquartered in Noida, India. Gujarat Fluorochemicals Limited is a subsidiary of Inox Leasing and Finance Limited.

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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.