FIZZ vs MNST

National Beverage Corp. vs Monster Beverage Corporation — Valuation Comparison 2026

FIZZ

Bottled & Canned Soft Drinks & Carbonated Waters
National Beverage Corp.
Quality
9.3
out of 10
Value Trap
18
SAFE
Price
$37.24
Last close
Models
12/13
Active
VS

MNST

Bottled & Canned Soft Drinks & Carbonated Waters
Monster Beverage Corporation
Quality
9.6
out of 10
Value Trap
6
SAFE
Price
$87.99
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType FIZZ Fair ValueFIZZ Upside MNST Fair ValueMNST Upside
Bayesian DCF Intrinsic $32.46 -12.8% $23.26 -73.6%
Earnings Power Value Intrinsic $19.04 -48.9% $20.92 -76.2%
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 FIZZ vs MNST — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FIZZ vs MNST — Which Stock Is More Undervalued?

MNST scores higher with a 9.6/10 quality rating vs FIZZ's 9.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing National Beverage Corp. (FIZZ) and Monster Beverage Corporation (MNST) 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.

FIZZ currently trades at $37.24 with a QOC of 9.3/10, while MNST trades at $87.99 with a QOC of 9.6/10.

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).