Arrow Greentech Limited (ARROWGREEN) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹8.9B
Fair value as of: Jun 29, 2026
Analysis
Arrow Greentech Limited (ARROWGREEN) currently trades at ₹588.80, while our model-based Fair Value estimate is ₹466.05 — implying the stock looks roughly 20.8% overvalued today. We read business quality at 96/100 (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
Arrow Greentech Limited, together with its subsidiaries, engages in the manufacture and sale of water-soluble films, bio-compostable products, and other green products in India and internationally. It operates through the Green Products and High-Tech Products segments. The company also offers packaging films for agro chemicals, liquid detergents, seed tapes, laundry bags, toilet blocks, and powder detergents. In addition, it provides embroidery films, mold release films, and water transfer printing films for the decoration of a range of products. Furthermore, the company offers plasticizer-free thermoplastic and transparent materials. Additionally, it provides security based and pharmaceutical products, and deals in anti-counterfeit solutions, IPRs, and other high-tech products, as well as intellectual property based products. Arrow Greentech Limited was formerly known as Arrow Coated Products Limited and changed its name to Arrow Greentech Limited in May 2016. The company was incor…
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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.