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Crest Nicholson Holdings (CRST) Fair Value & Analysis

Consumer Cyclical · GB · Market cap 169M GBX

Pricep0.7300
Fair Valuep0.1900
Upside-74.0%
Quality95/100
Evidence: Medium Range p0.1400 – p0.2400

Fair value as of: Jun 25, 2026

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Analysis

Crest Nicholson Holdings (CRST) currently trades at p0.7300, while our model-based Fair Value estimate is p0.1900 — implying the stock looks roughly 74.0% 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: medium).

About the company

Crest Nicholson Holdings plc engages in building residential homes in the United Kingdom. It develops and sells apartments, houses, and commercial properties. The company was founded in 1963 and is headquartered in Addlestone, United Kingdom.

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Frequently asked questions

Is Crest Nicholson Holdings (CRST) undervalued?
As of Jun 25, 2026, our model estimates a fair value of p0.1900 versus a price of p0.7300 — about −74% (overvalued). Model-based estimate, not financial advice.
What is the fair value of CRST?
Our 21-model fair value for Crest Nicholson Holdings is p0.1900 (as of Jun 25, 2026), built from audited fundamentals. The current price is p0.7300.
What is the quality score of CRST?
Crest Nicholson Holdings 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.