Is PDPA or PDX more undervalued in 2026?

CirclFi compares Pearl Diver Credit Company Inc. (PDPA) and 170604 (PDX) using 13 institutional-grade valuation models. PDPA has a Quality of Company score of 1.6/10 while PDX scores 1.7/10.

Which is a better buy — PDPA or PDX?

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 PDPA and PDX valuations compare?

PDPA at $25.19 and PDX at $21.55 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

PDPA vs PDX Valuation Comparison 2026 — Intrinsic Value Analysis

PDPA

Asset Management

Pearl Diver Credit Company Inc.

Quality

1.6

out of 10

Value Trap

—

Price

$25.19

Last close

Models

1/13

Active

PDX

Asset Management

170604

Quality

1.7

out of 10

Value Trap

—

Price

$21.55

Last close

Models

6/13

Active

Model-by-Model Comparison

Model	Type	PDPA Fair Value	PDPA Upside	PDX Fair Value	PDX Upside
Bayesian DCF	Intrinsic	—	—	$5.70	-73.5%
First Chicago	Scenario	$•••.••	••.•%	$•••.••	••.•%
Markov DDM	Intrinsic	$21.39	-15.2%	$13.99	-35.1%
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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PDPA vs PDX — Which Stock Is More Undervalued?

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

Comparing Pearl Diver Credit Company Inc. (PDPA) and 170604 (PDX) 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.

PDPA currently trades at $25.19 with a QOC of 1.6/10, while PDX trades at $21.55 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).