Is DLY or DMA more undervalued in 2026?

CirclFi compares DoubleLine Yield Opportunities (DLY) and DMA (DMA) using 13 institutional-grade valuation models. DLY has a Quality of Company score of 1.7/10 while DMA scores 1.8/10.

Which is a better buy — DLY or DMA?

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 DLY and DMA valuations compare?

DLY at $14.07 and DMA at $7.15 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

DLY vs DMA Valuation Comparison 2026 — Intrinsic Value Analysis

DLY

Asset Management

DoubleLine Yield Opportunities

Quality

1.7

out of 10

Value Trap

—

Price

$14.07

Last close

Models

6/13

Active

DMA

Asset Management

DMA

Quality

1.8

out of 10

Value Trap

—

Price

$7.15

Last close

Models

6/13

Active

Model-by-Model Comparison

Model	Type	DLY Fair Value	DLY Upside	DMA Fair Value	DMA Upside
Bayesian DCF	Intrinsic	$3.72	-73.5%	$1.89	-73.5%
First Chicago	Scenario	$•••.••	••.•%	$•••.••	••.•%
Markov DDM	Intrinsic	$12.24	-13.0%	$11.80	+65.0%
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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DLY vs DMA — Which Stock Is More Undervalued?

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

Comparing DoubleLine Yield Opportunities (DLY) and DMA (DMA) 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.

DLY currently trades at $14.07 with a QOC of 1.7/10, while DMA trades at $7.15 with a QOC of 1.8/10.

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).