Fairvalue-Calculator Fairvalue-Calculator
EN DE

John Laing Environmental Assets Group (FGEN) Fair Value & Analysis

Financial Services · GB · Market cap 519M GBX

Pricep0.8520
Fair Valuep1.52
Upside+78.4%
Quality95/100
Evidence: Low Range p1.14 – p1.91

Fair value as of: Jun 25, 2026

Analysis

John Laing Environmental Assets Group (FGEN) currently trades at p0.8520, while our model-based Fair Value estimate is p1.52 — implying the stock looks roughly 78.4% undervalued today. We read business quality at 95/100 (high quality), in the Financial Services 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: low) — always confirm before acting.

About the company

John Laing Environmental Assets Group Limited is a fund of John Laing Capital Management Limited.

Open the full interactive analysis →

Similar stocks

Frequently asked questions

Is John Laing Environmental Assets Group (FGEN) undervalued?
As of Jun 25, 2026, our model estimates a fair value of p1.52 versus a price of p0.8520 — about +78% (undervalued). Model-based estimate, not financial advice.
What is the fair value of FGEN?
Our 21-model fair value for John Laing Environmental Assets Group is p1.52 (as of Jun 25, 2026), built from audited fundamentals. The current price is p0.8520.
What is the quality score of FGEN?
John Laing Environmental Assets 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.