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Pinewood Technologies Group (PDGNF) Fair Value & Analysis

Consumer Cyclical · US · Market cap $376M

Price$3.23
Fair Value$3.18
Upside-1.5%
Quality95/100
Evidence: High Range $2.25 – $4.11

Fair value as of: Jun 24, 2026

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Analysis

Pinewood Technologies Group (PDGNF) currently trades at $3.23, while our model-based Fair Value estimate is $3.18 — implying the stock looks roughly 1.5% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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: high).

About the company

Pinewood Technologies Group PLC operates as a cloud-based dealer management software provider that offers software solutions to the automotive industry in the United Kingdom and internationally. It offers end-to-end solution that empowers vehicle retailers with efficient business processes. The company was formerly known as Pendragon PLC and changed its name to Pinewood Technologies Group PLC in February 2024. Pinewood Technologies Group PLC was founded in 1981 and is headquartered in Nottingham, the United Kingdom.

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Frequently asked questions

Is Pinewood Technologies Group (PDGNF) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $3.18 versus a price of $3.23 — about −2% (overvalued). Model-based estimate, not financial advice.
What is the fair value of PDGNF?
Our 21-model fair value for Pinewood Technologies Group is $3.18 (as of Jun 24, 2026), built from audited fundamentals. The current price is $3.23.
What is the quality score of PDGNF?
Pinewood Technologies Group 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.