GTY vs MLP

Getty Realty Corporation vs Maui Land & Pineapple Company, — Valuation Comparison 2026

GTY

Real Estate
Getty Realty Corporation
Quality
8.6
out of 10
Value Trap
24
SAFE
Price
$32.53
Last close
Models
13/13
Active
VS

MLP

Real Estate
Maui Land & Pineapple Company,
Quality
6.6
out of 10
Value Trap
6
SAFE
Price
$16.93
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType GTY Fair ValueGTY Upside MLP Fair ValueMLP Upside
Bayesian DCF Intrinsic $18.72 -42.4% $3.28 -80.7%
Earnings Power Value Intrinsic $3.42 -89.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $3.95 -87.9% $1.77 -89.5%
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 GTY vs MLP — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

GTY vs MLP — Which Stock Is More Undervalued?

GTY scores higher with a 8.6/10 quality rating vs MLP's 6.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Getty Realty Corporation (GTY) and Maui Land & Pineapple Company, (MLP) 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.

GTY currently trades at $32.53 with a QOC of 8.6/10, while MLP trades at $16.93 with a QOC of 6.6/10.

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).