MSN vs SONO

Emerson Radio Corporation vs Sonos, Inc. — Valuation Comparison 2026

MSN

Household Audio & Video Equipment
Emerson Radio Corporation
Quality
6.1
out of 10
Value Trap
24
SAFE
Price
$0.42
Last close
Models
11/13
Active
VS

SONO

Household Audio & Video Equipment
Sonos, Inc.
Quality
9.1
out of 10
Value Trap
13
SAFE
Price
$15.78
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType MSN Fair ValueMSN Upside SONO Fair ValueSONO Upside
Bayesian DCF Intrinsic $0.06 -85.0% $13.23 -16.2%
Earnings Power Value Intrinsic $0.25 -42.9% $12.89 -18.3%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for MSN vs SONO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MSN vs SONO — Which Stock Is More Undervalued?

SONO scores higher with a 9.1/10 quality rating vs MSN's 6.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Emerson Radio Corporation (MSN) and Sonos, Inc. (SONO) 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.

MSN currently trades at $0.42 with a QOC of 6.1/10, while SONO trades at $15.78 with a QOC of 9.1/10.

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).