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Kestrel Group (KG) Fair Value & Analysis

Financial Services · US · Market cap $93.8M

Price$10.91
Fair Value$16.76
Upside+53.6%
Quality95/100
Evidence: High Range $12.57 – $20.95

Fair value as of: Jun 26, 2026

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Analysis

Kestrel Group (KG) currently trades at $10.91, while our model-based Fair Value estimate is $16.76 — implying the stock looks roughly 53.6% 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: high) — always confirm before acting.

About the company

Kestrel Group Ltd engages in provision of fronting services to insurance program managers, managing general agencies, reinsurers, and reinsurance brokers in Bermuda. The company operates through two segments: Program Services and Legacy Reinsurance. The company is based in Hamilton, Bermuda.

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Frequently asked questions

Is Kestrel Group (KG) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $16.76 versus a price of $10.91 — about +54% (undervalued). Model-based estimate, not financial advice.
What is the fair value of KG?
Our 21-model fair value for Kestrel Group is $16.76 (as of Jun 26, 2026), built from audited fundamentals. The current price is $10.91.
What is the quality score of KG?
Kestrel 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.