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Maschinenfabrik HEID AG (HED) Fair Value & Analysis

Industrials · AT · Market cap €3.3M

Price€1.00
Fair Value€0.5200
Upside-48.0%
Quality95/100
Evidence: Medium Range €0.3900 – €0.6500

Fair value as of: Jun 24, 2026

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Analysis

Maschinenfabrik HEID AG (HED) currently trades at €1.00, while our model-based Fair Value estimate is €0.5200 — implying the stock looks roughly 48.0% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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

Maschinenfabrik HEID AG operates as a machine tool manufacturing company in Austria and internationally. It is involved in the rental of machinery; service and modernization of special machines; and sale of DVS Group machines. The company was founded in 1883 and is based in Stockerau, Austria.

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Frequently asked questions

Is Maschinenfabrik HEID AG (HED) undervalued?
As of Jun 24, 2026, our model estimates a fair value of €0.5200 versus a price of €1.00 — about −48% (overvalued). Model-based estimate, not financial advice.
What is the fair value of HED?
Our 21-model fair value for Maschinenfabrik HEID AG is €0.5200 (as of Jun 24, 2026), built from audited fundamentals. The current price is €1.00.
What is the quality score of HED?
Maschinenfabrik HEID AG has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.