Nanologica AB (NICA) Fair Value & Analysis
Healthcare · SE · Market cap 174M SEK
Fair value as of: Jun 24, 2026
Analysis
Nanologica AB (NICA) currently trades at kr 0.5460, while our model-based Fair Value estimate is kr 0.3100 — implying the stock looks roughly 43.2% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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: low).
About the company
Nanologica AB (publ), a life science tools company, develops, manufactures, and sells nanoporous silica particles in China, India, Turkey, the United States, and internationally. The company offers NLAB Saga, a silica-based purification media for preparative chromatography that is developed for the purification of peptide drugs, such as insulin and GLP-1 analogues; NLAB Idun, an ion exchange product for robust, reproducible, and efficient downstream purification of GLP-1 analogues and other peptides; NLAB Idun SP, a strong cation exchanger with sulfopropyl groups as ligands; NLAB Idun Q, a strong anion exchanger with a quaternary amine ligand; and NLAB Siv, a non-silica-based media for purification by preparative chromatography used for products outside the peptide range. It also provides high-performance liquid chromatography, a separation method based on different substances in a solution passing through a column at different paces; and analytical chromatography, an analysis metho…
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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.