AlphaMadera's AlphaVal page classifies SIGA Technologies, Inc. as a Platform & Compounding FCF business and values it using Two-stage FCF DCF, then compares the result to the current market price to flag SIGA as undervalued, fairly valued, or overvalued.

What is SIGA Technologies, Inc.'s fair value?

Fair value for SIGA comes from a Two-stage FCF DCF model -- the approach AlphaVal selected for this company's Platform & Compounding FCF classification. The live AlphaVal page shows bear, base, and bull scenarios alongside the key assumption behind each.

How does AlphaMadera value SIGA?

AlphaVal routes each company to one of ten valuation archetypes based on its business model. SIGA was classified as Platform & Compounding FCF and is valued using Two-stage FCF DCF, built from SIGA's most recent reported fundamentals.

SIGA - SIGA Technologies, Inc.

Price: -- -- | CONSENSUS: Buy DETAILS

AlphaVal

Deterministic, archetype-aware fair value

Platform & Compounding FCF 85% confidence

Primary model: Two-stage FCF DCF

Valuation Signal Undervalued Strong

Trading 85.7% below fair value

Current Price $3.15

Bear Case $14.27 352.4% upside ($14.27 - $3.15) / $3.15 = 352.4% 10% stage 1 growth, 11% discount

Fair Value $22.14 601.7% upside ($22.14 - $3.15) / $3.15 = 601.7% 17% stage 1 growth, 11% discount

Bull Case $31.26 890.9% upside ($31.26 - $3.15) / $3.15 = 890.9% 22% stage 1 growth, 11% discount

Adjust Assumptions

DCF Stage 1 Growth Rate

16.6%

Discount Rate (WACC)

11.0%

Terminal Growth Rate

3.0%

Key Value Driver

FCF growth rate (17% base case)

Terminal Value % of EV 44%

Implied Market Multiple 1.8x

Market is pricing in (growth) -30.5% vs our 16.7% base

Plain-Language Summary

Using a two-stage FCF DCF with 17% growth decelerating over 15 years, discounted at 11%, the base-case intrinsic value is $22.14 per share.

Warnings

Key Risks

P/E alone misleads — earnings depressed by growth investment
Cyclical or commodity businesses may be misclassified as platforms
Terminal value dominance suggests sensitivity to long-run assumptions