First Capital S.p.A (FIC) Fair Value & Analysis
Financial Services · IT · Market cap €58.5M
Fair value as of: Jun 26, 2026
Analysis
First Capital S.p.A (FIC) currently trades at €16.80, while our model-based Fair Value estimate is €33.60 — implying the stock looks roughly 100.0% undervalued today. We read business quality at 85/100 (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: medium) — always confirm before acting.
About the company
First Capital S.p.A. is a private equity firm specializing in public equity and private equity investments, mature, buyout, growth capital, and PIPEs investments in small/medium sized companies. The firm invests in different types of financial instruments: ordinary shares, special shares, convertible bonds, and bonds cum warrants. The firm seeks to acquire equity positions in enterprises that are either already listed or in the pre-IPO phase. The firm has no industry limitations. It invests in all companies based in Italy. It considers investments in manufacturing and service sectors. The firm prefers to invest in companies having EBITDA minimum of "5 million ($5.43 million), EBITDA more than 10%, ROCE greater than 10% and revenue between "50 million ($54.35 million) to "150 million ($163.04 million). It prefers to take majority stake. First Capital S.p.A. was founded in February 2008 and is based in Milan, Italy.
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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.