Maral Overseas Limited (MARALOVER) Fair Value & Analysis

Consumer Cyclical · IN · Market cap ₹2.2B

A solid business, but screening 67% overvalued on our models.

What matters now

• The price sits above even our optimistic bull case (₹21.61). The favourable scenario is already priced in.
• Solid but not exceptional quality (52/100) and above fair value, neither a clear bargain nor a standout compounder.
• A fairly wide model range (₹10.02 to ₹21.61) leaves room in how you read the outcome.

Price vs Fair Value (5 years)

White line = price, green steps = our fair value per fiscal year, dashed = 300-day average. As of Aug 13, 2026.

How to read this chart

60‑month range ₹32.18 – ₹128.08 · fair‑value band ₹10.02 – ₹21.61 · the ₹53.15 price screens above the ₹17.29 fair value. Dashed = 300-day average. As of Aug 13, 2026.

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Analysis

Maral Overseas Limited (MARALOVER) currently trades at ₹53.15, while our model-based Fair Value estimate is ₹17.29, implying the stock looks roughly 67.5% overvalued today. The Quality Score stands at 52/100 (solid 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: medium).

Over the trailing twelve months, Maral Overseas Limited generated revenue of ₹9.8B at a net margin of 0.3%. Revenue declined 6.0% year over year. It earns a return on equity of 3.0%. Net debt stands at ₹4.0B. Fundamentals as of Aug 13, 2026

Our scenario range runs from ₹10.02 (bear case) to ₹21.61 (bull case); at ₹53.15, the current price sits above that range. Bear and bull are the same models run on conservative and optimistic assumptions (margins, growth, valuation multiples), so a plausible valuation range, not a price target. The share trades about 32% below its 52-week high and 56% above its 52-week low, currently above its 200-day average. For context, the median of 10 Consumer Cyclical peers we cover trades at -7% fair-value upside, at -67%, MARALOVER screens richer than that median.

Fair Value models

Each model estimates fair value its own way; the Fair Value above is the evidence-weighted blend. Evidence (0–100) measures how completely this model’s inputs are available: well-fed models carry more weight in the blend. The spread across models is intentional, each one stresses a different value driver; dividend models, for instance, come out structurally low when payout is small.

Widest divergence: DCF Models (₹67.77) versus Earnings-Based (₹12.22). Highest evidence: Growth DCF (80).

Key figures & financial health

Quality Score breakdown

About the company

Maral Overseas Limited manufactures and sell yarns, fabrics, and garments in India, North America, Europe, Gulf and the Middle East, the Far East and South East Asia, Africa, and internationally.

Full company description

Maral Overseas Limited manufactures and sell yarns, fabrics, and garments in India, North America, Europe, Gulf and the Middle East, the Far East and South East Asia, Africa, and internationally. The company offers melange, single, double, dyed, combed and carded cotton, polyester/cotton blended, multifold, viscose/birla viscose blends, modal/birla modal and blends, lyocell and blends, bamboo and blends, acrylic and blends, cotton/nylon blends, triblends, miyabi blended, giza, pima/supima, contamination free, BCI, organic cotton, recycle cotton and polyester, compact, slub, injected slub, core spun, eli and zero twist, reverse twist, P/C siro/mock twist, and synthetic and cellulosic blend yarns. Its yarn products are used in various applications, such as circular and socks knitting, flat knits, home furnishing, towel weaving, carpets and rugs, denims, industrial and bottom weight fabrics, suiting and shirts, yarn dyeing, and weaving. The company also provides cotton fabrics in various knits, such as single jersey, rib, interlock, piquet, French rib, pointelle, and autostriper/engineered stripe; honey combs, fleece, plaited and variegated structured, and feeder and engineered stripe fabrics; spandex fabrics in various knits, including single jersey, rib, interlock, piquet, and fleece; special fibers and yarns comprising bamboo and blends, soya and blends, organic cotton, fairtrade certified cotton, polyester, slub fabric, modal/birla modal and blends, and lyocell and blends; and special finishes. In addition, it offers a range of garments consisting of active and casual wear, and sleepwear for men and ladies; fair trade garments and soft toys for infants and kids; and various home accessories. Maral Overseas Limited was incorporated in 1989 and is headquartered in Noida, India.

Company description, as reported by the company or data provider.

Revenue & earnings trend

FY2022 – FY2026 · reported fiscal years

Maral Overseas Limited reported revenue of ₹9.8B in FY2026 versus ₹10.6B in FY2022, a compound −1.9%/yr. Reported net income was ₹32.6M in FY2026, compounding −53.0%/yr from FY2022.

MARALOVER screens 67% overvalued. Compare with Shenzhou International Group →

Peer Group

Textile Manufacturing · 317 stocks

How this stock ranks against its industry: the green marker is this stock, the band is the typical 25–75% peer range, and the tick is the median.

Valuation Multiples vs Textile Manufacturing median · lower = cheaper

Snowflake

Five quick dimensions, each 0 to 100: VALUE (fair-value potential), FUTURE (revenue growth), PAST (return on equity), HEALTH (low debt), DIVIDEND (yield). Green = this stock, grey = typical sector peer.

VALUE 0: the price sits above our fair-value range.

Values & ESG

Does this company touch areas you may want to avoid? The classification is inferred from sector and industry.

ESG scores are not available for this stock yet. Values and ESG data are contextual and can differ between providers.

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Frequently asked questions

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.