Octave Specialty Group (OSG) Fair Value & Analysis
Financial Services · US · Market cap $259M
Fair value as of: Jun 26, 2026
Analysis
Octave Specialty Group (OSG) currently trades at $6.15, while our model-based Fair Value estimate is $8.71 — implying the stock looks roughly 41.6% undervalued today. We read business quality at 80/100 (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
Octave Specialty Group, Inc., an insurance holding company, primarily engages in the specialty property and casualty insurance business in the United States and the United Kingdom. It operates in two segments, Specialty Property and Casualty Insurance; and Insurance Distribution. The Specialty Property and Casualty Insurance segment provides specialty property and casualty program insurance with a focus on commercial and personal liability risks. The Insurance Distribution segment offers property, niche specialty risk, accident and health, miscellaneous specialty, reinsurance, surety, marine and energy, specialty auto, excess and surplus lines commercial package, professional lines, and directors' and officers' insurance. The company was formerly known as Ambac Financial Group, Inc. and changed its name to Octave Specialty Group, Inc. in November 2025. The company was incorporated in 1991 and is headquartered in New York, New York.
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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.