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Italy Innovazioni S.p.A (MLITN) Fair Value & Analysis

Industrials · FR · Market cap €30.8M

Price€8.05
Fair Value€4.69
Upside-41.7%
Quality92/100
Evidence: Low Range €3.52 – €5.87

Fair value as of: Jun 24, 2026

Analysis

Italy Innovazioni S.p.A (MLITN) currently trades at €8.05, while our model-based Fair Value estimate is €4.69 — implying the stock looks roughly 41.7% overvalued today. We read business quality at 92/100 (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: low).

About the company

Italy Innovazioni S.p.A. operates an intellectual property business company, engages in the design, prototyping, production, and marketing of electric outlets in Italy and internationally. The company offers HIDE, a smart socket that hides the plug. Italy Innovazioni S.p.A. was founded in 2012 and is based in Rome, Italy.

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Frequently asked questions

Is Italy Innovazioni S.p.A (MLITN) undervalued?
As of Jun 24, 2026, our model estimates a fair value of €4.69 versus a price of €8.05 — about −42% (overvalued). Model-based estimate, not financial advice.
What is the fair value of MLITN?
Our 21-model fair value for Italy Innovazioni S.p.A is €4.69 (as of Jun 24, 2026), built from audited fundamentals. The current price is €8.05.
What is the quality score of MLITN?
Italy Innovazioni S.p.A has a Quality Score of 92/100, 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.