HICL Infrastructure PLC (HICL) Fair Value & Analysis
Financial Services · GB · Market cap 2.5B GBX
Analysis
HICL Infrastructure PLC (HICL) currently trades at p1.34, while our model-based Fair Value estimate is p2.25 — implying the stock looks roughly 68.2% undervalued today. We read business quality at 97/100 (high quality), in the Financial Services 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
HICL Infrastructure PLC is an infrastructure investment firm specializes in direct and fund of funds investments. For direct investments, it seeks to invest in infrastructure projects. It invests in project companies which have not yet completed the construction phases of their concessions including project companies which are in the process of bidding for project concessions. The fund also invests project companies with "demand' based concessions and project companies which do not have public sector sponsored/awarded or government backed concessions. It seeks to invest in PFI, PPP, P3, social infrastructure projects, toll roads, bridges, and tunnels, airports, ports, utilities, communication networks, and renewables. The fund makes fund of funds investments in limited partnerships and other funds that make infrastructure investments and financial instruments and securities issued by companies that make infrastructure investments, or whose activities are similar or comparable to inf…
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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.