H&R GmbH & Co (2HRA) Fair Value & Analysis
Basic Materials · DE · Market cap €176M
Fair value as of: Jun 25, 2026
Analysis
H&R GmbH & Co (2HRA) currently trades at €4.80, while our model-based Fair Value estimate is €2.85 — implying the stock looks roughly 40.6% overvalued today. We read business quality at 89/100 (high quality), in the Basic Materials 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
H&R GmbH & Co. KGaA engages in the production and sale of chemical-pharmaceutical raw materials and injection molded precision plastic parts worldwide. It operates through three segments: ChemPharm Refining, ChemPharm Sales, and Plastics. The ChemPharm Refining segment offers paraffins, white oils, plasticizers, base oils, lubricants, and other crude-oil based specialty products, as well as bitumen, feedstocks, and bunker fuel. The ChemPharm Sales segment provides paraffins, plasticizers, wax emulsions, and other crude-oil based specialty products. The Plastics segment develops, manufactures, and sells high-precision plastic parts. The company also provides petroleum jellies, cosmetic and pharmaceutical specialties, process oils, and cable fillers, as well as polymers and APP based products for the construction industry. The company was formerly known as H&R AG and changed its name to H&R GmbH & Co. KGaA in August 2016. H&R GmbH & Co. KGaA was founded in 1919 and is headquartered in…
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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.