Is DBL or DLY more undervalued in 2026?

CirclFi compares DoubleLine Opportunistic Credit (DBL) and DoubleLine Yield Opportunities (DLY) using 13 institutional-grade valuation models. DBL has a Quality of Company score of 1.7/10 while DLY scores 1.7/10.

Which is a better buy — DBL or DLY?

Compare intrinsic values from 13 independent models against current market prices. CirclFi also calculates Value Trap scores. This is not financial advice — conduct your own analysis.

How do DBL and DLY valuations compare?

DBL at $14.37 and DLY at $14.07 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

DBL vs DLY Valuation Comparison 2026 — Intrinsic Value Analysis

DBL

Asset Management

DoubleLine Opportunistic Credit

Quality

1.7

out of 10

Value Trap

—

Price

$14.37

Last close

Models

6/13

Active

DLY

Asset Management

DoubleLine Yield Opportunities

Quality

1.7

out of 10

Value Trap

—

Price

$14.07

Last close

Models

6/13

Active

Model-by-Model Comparison

Model	Type	DBL Fair Value	DBL Upside	DLY Fair Value	DLY Upside
Bayesian DCF	Intrinsic	$3.80	-73.5%	$3.72	-73.5%
First Chicago	Scenario	$•••.••	••.•%	$•••.••	••.•%
Markov DDM	Intrinsic	$11.54	-19.7%	$12.24	-13.0%
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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DBL vs DLY — Which Stock Is More Undervalued?

Both DBL and DLY score 1.7/10 on quality. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing DoubleLine Opportunistic Credit (DBL) and DoubleLine Yield Opportunities (DLY) 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.

DBL currently trades at $14.37 with a QOC of 1.7/10, while DLY trades at $14.07 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).