KIO vs KYN

KKR Income Opportunities Fund vs Kayne Anderson MLP/Midstream In — Valuation Comparison 2026

KIO

Asset Management
KKR Income Opportunities Fund
Quality
1.7
out of 10
Value Trap
Price
$11.39
Last close
Models
6/13
Active
VS

KYN

Asset Management
Kayne Anderson MLP/Midstream In
Quality
2.0
out of 10
Value Trap
Price
$13.85
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType KIO Fair ValueKIO Upside KYN Fair ValueKYN Upside
Bayesian DCF Intrinsic $3.02 -73.5% $4.09 -70.5%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $12.86 +15.2%
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 $0.28 -98.1%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

KIO vs KYN — Which Stock Is More Undervalued?

KYN scores higher with a 2.0/10 quality rating vs KIO's 1.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing KKR Income Opportunities Fund (KIO) and Kayne Anderson MLP/Midstream In (KYN) 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.

KIO currently trades at $11.39 with a QOC of 1.7/10, while KYN trades at $13.85 with a QOC of 2.0/10.

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).