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Calculus VCT plc (CLC) Fair Value & Analysis

Financial Services · GB · Market cap 51.9M GBX

Pricep0.5325
Fair Valuep0.2300
Upside-56.8%
Quality95/100
Evidence: High Range p0.1700 – p0.2800

Fair value as of: Jun 26, 2026

Analysis

Calculus VCT plc (CLC) currently trades at p0.5325, while our model-based Fair Value estimate is p0.2300 — implying the stock looks roughly 56.8% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services 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

Calculus VCT plc, formerly known as Investec Structured Products Calculus VCT PLC, is a venture capital trust specializing in venture capital investments. The firm prefers to invest in UK regions. The firm seek to invest in Technology, Healthcare and Entertainment sectors.

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Frequently asked questions

Is Calculus VCT plc (CLC) undervalued?
As of Jun 26, 2026, our model estimates a fair value of p0.2300 versus a price of p0.5325 — about −57% (overvalued). Model-based estimate, not financial advice.
What is the fair value of CLC?
Our 21-model fair value for Calculus VCT plc is p0.2300 (as of Jun 26, 2026), built from audited fundamentals. The current price is p0.5325.
What is the quality score of CLC?
Calculus VCT plc 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.