Fidia S.p.A (FDA) Fair Value & Analysis
Industrials · IT · Market cap €9.7M
Fair value as of: Jun 26, 2026
Analysis
Fidia S.p.A (FDA) currently trades at €0.0096, while our model-based Fair Value estimate is €0.0096 — implying the stock looks roughly 0.4% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
Fidia S.p.A., together with its subsidiaries, designs, manufactures, and sells high speed milling systems, numerical controls, milling heads, and software systems. The company offers HMS, a device for measuring and compensating geometric error on continuous or indexed bi-rotary heads and roto-tilting tables; TMSC, a device to measure length and diameter of the tool, as well as to check the shape; pushbutton panels; XPower digital drives for axis and spindle movement; and I/O Line input/output modules. It also provides software solutions include ViMill, an anti-collision solution; Machine Monitor, a software to monitor NC variables and parameters; Velocity 6, a solution for axes control to enhance the performances of the machine; HiMill, a CAM software for the machining of dies, models, and aeronautical components; Isograph solution, a user interface; and procedure-PRX, a solution for customized automation. It serves automotive, aerospace, and power generation industries in Italy, Eu…
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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.