Banswara Syntex Limited (BANSWRAS) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹4.6B
Fair value as of: Jun 29, 2026
Analysis
Banswara Syntex Limited (BANSWRAS) currently trades at ₹133.15, while our model-based Fair Value estimate is ₹165.80 — implying the stock looks roughly 24.5% undervalued today. We read business quality at 96/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Banswara Syntex Limited engages in the production and sale of textile products in India and internationally. It provides yarn products, such as polyester, viscose, acrylic, wool, polyester/viscose, polyester/viscose wool, polyester/viscose lycra, polyester/viscose linen, and polyester/viscose high twists yarns; cotton, worsted, jacquard, and knitted fabrics; and readymade garments, including trousers, jackets, and waistcoats. The company also offers finish fabric; technical fabric used in clothing, furniture, hygiene medicals, and construction material applications; automotive fabric; and fire-retardant fabric used as curtains, upholstery, drapes, wall paneling, cushion covers, sheets and as lining for tents, as well as for furnishing of auditoriums, multiplexes, cinema halls, hotels, railway coaches, airlines, ships and cruise, and buses and coaches. Banswara Syntex Limited was incorporated in 1976 and is based in Mumbai, India.
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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.