RHP vs RLJ

Ryman Hospitality Properties, I vs RLJ Lodging Trust — Valuation Comparison 2026

RHP

Real Estate Investment Trusts
Ryman Hospitality Properties, I
Quality
8.1
out of 10
Value Trap
6
SAFE
Price
$115.13
Last close
Models
11/13
Active
VS

RLJ

Real Estate Investment Trusts
RLJ Lodging Trust
Quality
6.2
out of 10
Value Trap
14
SAFE
Price
$9.73
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType RHP Fair ValueRHP Upside RLJ Fair ValueRLJ Upside
Bayesian DCF Intrinsic $1.90 -98.3% $2.82 -66.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $100.62 -12.6% $9.39 -3.5%
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 RHP vs RLJ — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

RHP vs RLJ — Which Stock Is More Undervalued?

RHP scores higher with a 8.1/10 quality rating vs RLJ's 6.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Ryman Hospitality Properties, I (RHP) and RLJ Lodging Trust (RLJ) 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.

RHP currently trades at $115.13 with a QOC of 8.1/10, while RLJ trades at $9.73 with a QOC of 6.2/10.

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).