PI Industries Limited (PIIND) Fair Value & Analysis
Basic Materials · IN · Market cap ₹412B
Analysis
PI Industries Limited (PIIND) currently trades at ₹2,767, while our model-based Fair Value estimate is ₹1,345 — implying the stock looks roughly 51.4% overvalued today. We read business quality at 97/100 (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
PI Industries Limited, together with its subsidiaries, manufactures and distributes of agricultural chemicals in India, rest of Asia, North America, Europe, and internationally. It operates through Agro Chemicals and Pharma segments. The company offers agrochemicals, including insecticides, fungicides, herbicides, and biologicals; crop solutions for soybeans, chili, sugarcane, rice, wheat, cotton, and corn, as well as horticulture products; and plant nutrients and specialty chemicals. It also provides research and development services, such as target discovery, molecule design, library synthesis, lead optimization, biological evaluation, and route synthesis. In addition, the company offers custom synthesis and manufacturing solutions, including process research and development, analytical method development, synthesis of reference standards, structure elucidation and synthesis of impurities, physio-chemical studies and 5-batch analysis under GLP conditions, scale-up studies, safety …
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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.