LAMR vs LAND

Lamar Advertising Company vs Gladstone Land Corporation — Valuation Comparison 2026

LAMR

Real Estate Investment Trusts
Lamar Advertising Company
Quality
8.4
out of 10
Value Trap
24
SAFE
Price
$152.46
Last close
Models
12/13
Active
VS

LAND

Real Estate Investment Trusts
Gladstone Land Corporation
Quality
6.0
out of 10
Value Trap
12
SAFE
Price
$9.48
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType LAMR Fair ValueLAMR Upside LAND Fair ValueLAND Upside
Bayesian DCF Intrinsic $46.35 -69.6% $2.00 -78.9%
Earnings Power Value Intrinsic $3.49 -97.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $889.00 +483.1% $2.65 -72.0%
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 LAMR vs LAND — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

LAMR vs LAND — Which Stock Is More Undervalued?

LAMR scores higher with a 8.4/10 quality rating vs LAND's 6.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Lamar Advertising Company (LAMR) and Gladstone Land Corporation (LAND) 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.

LAMR currently trades at $152.46 with a QOC of 8.4/10, while LAND trades at $9.48 with a QOC of 6.0/10.

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).