Rail Vikas Nigam Limited (RVNL) Fair Value & Analysis
Industrials · IN · Market cap ₹491B
Analysis
Rail Vikas Nigam Limited (RVNL) currently trades at ₹240.13, while our model-based Fair Value estimate is ₹61.85 — implying the stock looks roughly 74.2% 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
Rail Vikas Nigam Limited, together with its subsidiaries, engages in rail infrastructure works in India and internationally. The company undertakes rail project development and implementation, as well as provides financial resources mobilization services. It also executes various railway projects, including new lines, doubling, gauge conversion, railway electrification, workshops, bridge work, mega and monumental bridges, metro and metropolitan transport projects, new lines, hilly railway projects, construction of cable stayed bridges, institutional buildings, track renewal, training institutes, railway and other safety works, traffic facilities, and road over bridges, etc. In addition, the company engages in civil engineering; equipment and engine; installation of solar energy systems, and electricity transmission and control apparatus; installation and maintenance of underwater telecommunications and power cables; contracting of electrical fittings, ports and marine construction, …
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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.