HUN vs OLN

Huntsman Corporation vs Olin Corporation — Valuation Comparison 2026

HUN

Chemicals
Huntsman Corporation
Quality
6.3
out of 10
Value Trap
3
SAFE
Price
$15.47
Last close
Models
13/13
Active
VS

OLN

Chemicals
Olin Corporation
Quality
4.4
out of 10
Value Trap
24
SAFE
Price
$26.75
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType HUN Fair ValueHUN Upside OLN Fair ValueOLN Upside
Bayesian DCF Intrinsic $5.28 -65.8% $110.49 +313.0%
Earnings Power Value Intrinsic $12.19 -16.7% $44.03 +53.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for HUN vs OLN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

HUN vs OLN — Which Stock Is More Undervalued?

HUN scores higher with a 6.3/10 quality rating vs OLN's 4.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Huntsman Corporation (HUN) and Olin Corporation (OLN) 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.

HUN currently trades at $15.47 with a QOC of 6.3/10, while OLN trades at $26.75 with a QOC of 4.4/10.

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).