Is HLXC or IACO more undervalued in 2026?

CirclFi compares Helix Acquisition Corp. III (HLXC) and Idea Acquisition Corp. (IACO) using 13 institutional-grade valuation models. HLXC has a Quality of Company score of 3.3/10 while IACO scores 3.1/10.

Which is a better buy — HLXC or IACO?

Compare intrinsic values from 13 independent models against current market prices. CirclFi also calculates Value Trap scores. This is not financial advice — conduct your own analysis.

How do HLXC and IACO valuations compare?

HLXC at $10.21 and IACO at $9.89 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

HLXC vs IACO Valuation Comparison 2026 — Intrinsic Value Analysis

HLXC

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Helix Acquisition Corp. III

Quality

3.3

out of 10

Value Trap

—

Price

$10.21

Last close

Models

6/13

Active

IACO

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Idea Acquisition Corp.

Quality

3.1

out of 10

Value Trap

—

Price

$9.89

Last close

Models

6/13

Active

Model-by-Model Comparison

Model	Type	HLXC Fair Value	HLXC Upside	IACO Fair Value	IACO Upside
Bayesian DCF	Intrinsic	$2.70	-73.6%	$2.61	-73.6%
First Chicago	Scenario	$•••.••	••.•%	$•••.••	••.•%
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
PWERM	Option-Based	$9.47	-7.3%	$9.27	-6.3%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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HLXC vs IACO — Which Stock Is More Undervalued?

HLXC scores higher with a 3.3/10 quality rating vs IACO's 3.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Helix Acquisition Corp. III (HLXC) and Idea Acquisition Corp. (IACO) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

HLXC currently trades at $10.21 with a QOC of 3.3/10, while IACO trades at $9.89 with a QOC of 3.1/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).