IHG vs LVS

Intercontinental Hotels Group vs Las Vegas Sands Corp. — Valuation Comparison 2026

IHG

Hotels & Motels
Intercontinental Hotels Group
Quality
2.1
out of 10
Value Trap
Price
$154.88
Last close
Models
13/13
Active
VS

LVS

Hotels & Motels
Las Vegas Sands Corp.
Quality
8.4
out of 10
Value Trap
Price
$50.57
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType IHG Fair ValueIHG Upside LVS Fair ValueLVS Upside
Bayesian DCF Intrinsic $58.41 -62.3% $23.28 -54.0%
Earnings Power Value Intrinsic $102.01 -29.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $281.92 +83.6% $52.96 +4.7%
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 IHG vs LVS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

IHG vs LVS — Which Stock Is More Undervalued?

LVS scores higher with a 8.4/10 quality rating vs IHG's 2.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Intercontinental Hotels Group (IHG) and Las Vegas Sands Corp. (LVS) 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.

IHG currently trades at $154.88 with a QOC of 2.1/10, while LVS trades at $50.57 with a QOC of 8.4/10.

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).