Ahluwalia Contracts (India) Limited (AHLUCONT) Fair Value & Analysis
Industrials · IN · Market cap ₹57.0B
Fair value as of: Jun 29, 2026
Analysis
Ahluwalia Contracts (India) Limited (AHLUCONT) currently trades at ₹848.10, while our model-based Fair Value estimate is ₹833.46 — implying the stock looks roughly 1.7% overvalued today. We read business quality at 97/100 (high 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: high).
About the company
Ahluwalia Contracts (India) Limited, together with its subsidiaries, operates as an engineering, procurement, and construction company in India and internationally. The company operates through Construction Contract, Lease Rental, and Others segments. Its portfolio includes residential and commercial buildings/complexes, hotels, institutional and hospital buildings, corporate offices, information technology (IT) parks, industrial complexes, automated car parking lot, townships, BOT projects, metro station and depot, redevelopment/upgradation of railway stations, urban infrastructure, and data centres. The company is also involved in the developing and operating commercial complex; real estate trading business, as well as rentals activities. It serves central and state governments, including PSUs business house and real estate developers. The company was founded in 1965 and is based in New Delhi, 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.