OXLCO vs OXLCP

Oxford Lane Capital Corp. - Pre vs Oxford Lane Capital Corp. - 6.2 — Valuation Comparison 2026

OXLCO

Asset Management
Oxford Lane Capital Corp. - Pre
Quality
1.7
out of 10
Value Trap
Price
$24.09
Last close
Models
13/13
Active
VS

OXLCP

Asset Management
Oxford Lane Capital Corp. - 6.2
Quality
1.6
out of 10
Value Trap
Price
$24.99
Last close
Models
8/13
Active

Model-by-Model Comparison

ModelType OXLCO Fair ValueOXLCO Upside OXLCP Fair ValueOXLCP Upside
Bayesian DCF Intrinsic $3.18 -86.8% $61.67 +146.4%
Earnings Power Value Intrinsic $4.79 -79.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $1.95 -91.8% $16.78 -32.9%
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 OXLCO vs OXLCP — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

OXLCO vs OXLCP — Which Stock Is More Undervalued?

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

Comparing Oxford Lane Capital Corp. - Pre (OXLCO) and Oxford Lane Capital Corp. - 6.2 (OXLCP) 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.

OXLCO currently trades at $24.09 with a QOC of 1.7/10, while OXLCP trades at $24.99 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).