Netfonds AG (NF4) Fair Value & Analysis
Financial Services · DE · Market cap €183M
Fair value as of: Jun 26, 2026
Analysis
Netfonds AG (NF4) currently trades at €79.50, while our model-based Fair Value estimate is €13.47 — implying the stock looks roughly 83.1% overvalued today. We read business quality at 87/100 (high quality), in the Financial Services 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).
About the company
Netfonds AG, together with its subsidiaries, provides advisory services for the financial and insurance sectors in Germany. The company offers traditional asset management for private clients; and portfolio management of investment funds. It also operates a B2B platform in the finance and insurance sectors; and as a B2B2C service provider. In addition, the company provides billing model services comprising commission, variable service fees, service fees and commissions, fixed service fees, and fee-based consulting with credit to the client's account; customer loyalty, back office, legal certainty, customer acquisition, research, benefits, and basic knowledge services; finfire, a consultant software; and continuing education services, including online training courses, personal appointments, roadshows and trade fairs, workshops, and partner networks. It serves investment advisors, insurance brokers, banks, and organizations. Netfonds AG was founded in 2000 and is based in Hamburg, Ge…
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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.