BGX vs BGY

Blackstone GSO Long Short Credi vs Blackrock Enhanced Internationa — Valuation Comparison 2026

BGX

Asset Management
Blackstone GSO Long Short Credi
Quality
1.8
out of 10
Value Trap
Price
$10.92
Last close
Models
6/13
Active
VS

BGY

Asset Management
Blackrock Enhanced Internationa
Quality
1.7
out of 10
Value Trap
Price
$5.76
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType BGX Fair ValueBGX Upside BGY Fair ValueBGY Upside
Bayesian DCF Intrinsic $2.89 -73.5% $1.52 -73.5%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $8.57 -21.6% $17.51 +206.6%
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 $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for BGX vs BGY — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BGX vs BGY — Which Stock Is More Undervalued?

BGX scores higher with a 1.8/10 quality rating vs BGY's 1.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Blackstone GSO Long Short Credi (BGX) and Blackrock Enhanced Internationa (BGY) 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.

BGX currently trades at $10.92 with a QOC of 1.8/10, while BGY trades at $5.76 with a QOC of 1.7/10.

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).