SHIP vs TEN

Seanergy Maritime Holdings Corp vs Tsakos Energy Navigation Ltd — Valuation Comparison 2026

SHIP

Deep Sea Foreign Transportation of Freight
Seanergy Maritime Holdings Corp
Quality
2.1
out of 10
Value Trap
Price
$15.50
Last close
Models
13/13
Active
VS

TEN

Deep Sea Foreign Transportation of Freight
Tsakos Energy Navigation Ltd
Quality
7.8
out of 10
Value Trap
34
LOW
Price
$37.58
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType SHIP Fair ValueSHIP Upside TEN Fair ValueTEN Upside
Bayesian DCF Intrinsic $3.18 -79.5% $62.06 +65.2%
Earnings Power Value Intrinsic $5.73 -63.7% $23.78 -36.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
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 $•••.•• ••.•% $•••.•• ••.•%
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SHIP vs TEN — Which Stock Is More Undervalued?

TEN scores higher with a 7.8/10 quality rating vs SHIP's 2.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Seanergy Maritime Holdings Corp (SHIP) and Tsakos Energy Navigation Ltd (TEN) 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.

SHIP currently trades at $15.50 with a QOC of 2.1/10, while TEN trades at $37.58 with a QOC of 7.8/10.

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).