RBNE vs SFL

Robin Energy Ltd. vs SFL Corporation Ltd — Valuation Comparison 2026

RBNE

Deep Sea Foreign Transportation of Freight
Robin Energy Ltd.
Quality
4.2
out of 10
Value Trap
12
SAFE
Price
$1.10
Last close
Models
10/13
Active
VS

SFL

Deep Sea Foreign Transportation of Freight
SFL Corporation Ltd
Quality
6.7
out of 10
Value Trap
20
SAFE
Price
$11.04
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType RBNE Fair ValueRBNE Upside SFL Fair ValueSFL Upside
Bayesian DCF Intrinsic $25.06 +127.0%
Earnings Power Value Intrinsic $4.51 +178.4% $1.32 -88.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $5.17 +369.7% $14.09 +27.6%
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 RBNE vs SFL — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

RBNE vs SFL — Which Stock Is More Undervalued?

SFL scores higher with a 6.7/10 quality rating vs RBNE's 4.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Robin Energy Ltd. (RBNE) and SFL Corporation Ltd (SFL) 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.

RBNE currently trades at $1.10 with a QOC of 4.2/10, while SFL trades at $11.04 with a QOC of 6.7/10.

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).