Is RMM or RVI more undervalued in 2026?

CirclFi compares RiverNorth Managed Duration Mun (RMM) and Robinhood Ventures Fund I (RVI) using 13 institutional-grade valuation models. RMM has a Quality of Company score of 1.7/10 while RVI scores 1.7/10.

Which is a better buy — RMM or RVI?

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 RMM and RVI valuations compare?

RMM at $14.59 and RVI at $50.00 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

RMM vs RVI Valuation Comparison 2026 — Intrinsic Value Analysis

RMM

Asset Management

RiverNorth Managed Duration Mun

Quality

1.7

out of 10

Value Trap

—

Price

$14.59

Last close

Models

6/13

Active

RVI

Asset Management

Robinhood Ventures Fund I

Quality

1.7

out of 10

Value Trap

—

Price

$50.00

Last close

Models

5/13

Active

Model-by-Model Comparison

Model	Type	RMM Fair Value	RMM Upside	RVI Fair Value	RVI Upside
Bayesian DCF	Intrinsic	$3.86	-73.5%	$13.24	-73.5%
First Chicago	Scenario	$17.58	+22.9%	$71.22	+23.1%
Markov DDM	Intrinsic	$9.25	-34.8%	—	—
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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RMM vs RVI — Which Stock Is More Undervalued?

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

Comparing RiverNorth Managed Duration Mun (RMM) and Robinhood Ventures Fund I (RVI) 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.

RMM currently trades at $14.59 with a QOC of 1.7/10, while RVI trades at $50.00 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).