ELOG vs FRGT

Eastern International Ltd. vs Freight Technologies, Inc. — Valuation Comparison 2026

ELOG

Arrangement of Transportation of Freight & Cargo
Eastern International Ltd.
Quality
1.7
out of 10
Value Trap
Price
$0.85
Last close
Models
10/13
Active
VS

FRGT

Arrangement of Transportation of Freight & Cargo
Freight Technologies, Inc.
Quality
1.6
out of 10
Value Trap
Price
$4.36
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType ELOG Fair ValueELOG Upside FRGT Fair ValueFRGT Upside
Bayesian DCF Intrinsic $0.22 -73.7% $1.10 -74.7%
First Chicago Scenario $0.90 +7.1% $5.04 +21.3%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $0.81 -4.6% $16.20 +272.0%
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 ELOG vs FRGT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ELOG vs FRGT — Which Stock Is More Undervalued?

ELOG scores higher with a 1.7/10 quality rating vs FRGT's 1.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Eastern International Ltd. (ELOG) and Freight Technologies, Inc. (FRGT) 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.

ELOG currently trades at $0.85 with a QOC of 1.7/10, while FRGT trades at $4.36 with a QOC of 1.6/10.

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).