Is RA or RFM more undervalued in 2026?

CirclFi compares Brookfield Real Assets Income F (RA) and RiverNorth Flexible Municipal I (RFM) using 13 institutional-grade valuation models. RA has a Quality of Company score of 1.7/10 while RFM scores 1.7/10.

Which is a better buy — RA or RFM?

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 RA and RFM valuations compare?

RA at $12.82 and RFM at $14.61 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

RA vs RFM Valuation Comparison 2026 — Intrinsic Value Analysis

RA

Asset Management

Brookfield Real Assets Income F

Quality

1.7

out of 10

Value Trap

—

Price

$12.82

Last close

Models

6/13

Active

RFM

Asset Management

RiverNorth Flexible Municipal I

Quality

1.7

out of 10

Value Trap

—

Price

$14.61

Last close

Models

6/13

Active

Model-by-Model Comparison

Model	Type	RA Fair Value	RA Upside	RFM Fair Value	RFM Upside
Bayesian DCF	Intrinsic	$3.39	-73.5%	$3.87	-73.5%
First Chicago	Scenario	$•••.••	••.•%	$•••.••	••.•%
Markov DDM	Intrinsic	$15.18	+17.4%	$9.53	-34.8%
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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RA vs RFM — Which Stock Is More Undervalued?

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

Comparing Brookfield Real Assets Income F (RA) and RiverNorth Flexible Municipal I (RFM) 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.

RA currently trades at $12.82 with a QOC of 1.7/10, while RFM trades at $14.61 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).