SPML Infra Limited (SPMLINFRA) Fair Value & Analysis

Industrials · IN · Market cap ₹16.7B

Below-average quality, and screening another 27% overvalued on our models.

What matters now

• The price sits above even our optimistic bull case (₹187.75). The favourable scenario is already priced in.
• Weak quality (38/100) and above fair value at the same time, the margin of safety is missing on both counts.
• A fairly wide model range (₹101.24 to ₹187.75) 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 ₹9.25 – ₹307.97 · fair‑value band ₹101.24 – ₹187.75 · the ₹197.00 price screens above the ₹144.63 fair value. Dashed = 300-day average. As of Aug 13, 2026.

Full chart & analysis →

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Analysis

SPML Infra Limited (SPMLINFRA) currently trades at ₹197.00, while our model-based Fair Value estimate is ₹144.63, implying the stock looks roughly 26.6% overvalued today. The Quality Score stands at 38/100 (below-average quality), in the Industrials 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, SPML Infra Limited generated revenue of ₹8.7B at a net margin of 8.6%. Revenue grew 53.7% year over year. It earns a return on equity of 8.7%. Net debt stands at ₹1.9B. Fundamentals as of Aug 13, 2026

Our scenario range runs from ₹101.24 (bear case) to ₹187.75 (bull case); at ₹197.00, 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 39% below its 52-week high and 30% above its 52-week low, currently above its 200-day average. For context, the median of 10 Industrials peers we cover trades at -34% fair-value upside, at -27%, SPMLINFRA screens cheaper 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: Growth Earnings (₹144.63) versus DCF Models (₹1.48). Highest evidence: Residual Income (76).

Key figures & financial health

Quality Score breakdown

About the company

SPML Infra Limited operates as an infrastructure development company in India. The company undertakes water supply and bulk water transmission, wastewater and sanitation, and power distribution and rural electrification projects; constructs pumping stations and water reservoir; and offers metering and billing solutions, and battery energy storage systems, …

Full company description

SPML Infra Limited operates as an infrastructure development company in India. The company undertakes water supply and bulk water transmission, wastewater and sanitation, and power distribution and rural electrification projects; constructs pumping stations and water reservoir; and offers metering and billing solutions, and battery energy storage systems, as well as provides services in various areas, including construction of dams, canals, lift irrigation, and micro irrigation. It also undertakes power generation, transmission, and distribution projects, including the construction of hydro, solar, wind, gas turbine, and thermal power plants; and offers rural electrification, and integrated and smart energy management solutions. In addition, the company develops roads, bridges, flyovers, highways, industrial infrastructure, tunnels, special economic zones, industrial/business/technology parks, airports, bus terminals, automated car parking facilities, and toll express roads. Further, it provides municipal solid waste management solutions, such as collection, segregation, transportation, and safe disposal, as well as sewer rehabilitation solutions. Additionally, it develops an integrated management information system for metering, billing, CRM, network analysis, demand forecasting and management, asset and inventory management, business intelligence, and operation and maintenance of the entire network. The company was formerly known as Subhash Projects and Marketing Limited and changed its name to SPML Infra Limited in April 2010. SPML Infra Limited was incorporated in 1981 and is based in Kolkata, India.

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

Revenue & earnings trend

FY2022 – FY2026 · reported fiscal years

SPML Infra Limited reported revenue of ₹8.7B in FY2026 versus ₹9.5B in FY2022, a compound −2.3%/yr. Reported net income was ₹747M in FY2026, compounding +290.2%/yr from FY2022.

SPMLINFRA screens 27% overvalued. Compare with Larsen & Toubro Limited →

Peer Group

Engineering & Construction · 838 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 Engineering & Construction 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.