Is PW or RC more undervalued in 2026?

CirclFi compares Power REIT (MD) (PW) and Ready Capital Corporation (RC) using 13 institutional-grade valuation models. PW has a Quality of Company score of 6.1/10 while RC scores 5.9/10.

Which is a better buy — PW or RC?

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 PW and RC valuations compare?

PW at $0.78 and RC at $1.78 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

PW vs RC Valuation Comparison 2026 — Intrinsic Value Analysis

PW

Real Estate Investment Trusts

Power REIT (MD)

Quality

6.1

out of 10

Value Trap

LOW

Price

$0.78

Last close

Models

3/13

Active

RC

Real Estate Investment Trusts

Ready Capital Corporation

Quality

5.9

out of 10

Value Trap

LOW

Price

$1.78

Last close

Models

4/13

Active

Model-by-Model Comparison

Model	Type	PW Fair Value	PW Upside	RC Fair Value	RC Upside
EROIC Spread	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Markov DDM	Intrinsic	—	—	$3.58	+101.0%
ML-RIV	Intrinsic	$1.05	+34.1%	$1.77	-4.3%
PWERM	Option-Based	$1.29	+65.1%	—	—
Regime Cross-Sectional	Relative	$•••.••	••.•%	$•••.••	••.•%
FTNN Topology	Relative	$•••.••	••.•%	$•••.••	••.•%

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PW vs RC — Which Stock Is More Undervalued?

PW scores higher with a 6.1/10 quality rating vs RC's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Power REIT (MD) (PW) and Ready Capital Corporation (RC) 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.

PW currently trades at $0.78 with a QOC of 6.1/10, while RC trades at $1.78 with a QOC of 5.9/10.

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).