PSIG vs SGLY

PS International Group Ltd. vs Singularity Future Technology L — Valuation Comparison 2026

PSIG

Arrangement of Transportation of Freight & Cargo
PS International Group Ltd.
Quality
2.1
out of 10
Value Trap
Price
$8.30
Last close
Models
13/13
Active
VS

SGLY

Arrangement of Transportation of Freight & Cargo
Singularity Future Technology L
Quality
4.7
out of 10
Value Trap
32
LOW
Price
$0.39
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType PSIG Fair ValuePSIG Upside SGLY Fair ValueSGLY Upside
Bayesian DCF Intrinsic $1.55 -81.3% $0.38 -2.5%
Earnings Power Value Intrinsic $0.34 -94.6% $2.44 +425.2%
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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PSIG vs SGLY — Which Stock Is More Undervalued?

SGLY scores higher with a 4.7/10 quality rating vs PSIG's 2.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing PS International Group Ltd. (PSIG) and Singularity Future Technology L (SGLY) 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.

PSIG currently trades at $8.30 with a QOC of 2.1/10, while SGLY trades at $0.39 with a QOC of 4.7/10.

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).