CWH vs KMX

Camping World Holdings, Inc. vs CarMax Inc — Valuation Comparison 2026

CWH

Auto & Truck Dealerships
Camping World Holdings, Inc.
Quality
6.3
out of 10
Value Trap
32
LOW
Price
$7.66
Last close
Models
9/13
Active
VS

KMX

Auto & Truck Dealerships
CarMax Inc
Quality
5.9
out of 10
Value Trap
20
SAFE
Price
$43.90
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType CWH Fair ValueCWH Upside KMX Fair ValueKMX Upside
Bayesian DCF Intrinsic $21.32 +178.4%
Earnings Power Value Intrinsic $11.74 +51.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $134.35 +217.9%
Markov DDM Intrinsic $5.16 -32.6% $8.09 -78.9%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 CWH vs KMX — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CWH vs KMX — Which Stock Is More Undervalued?

CWH scores higher with a 6.3/10 quality rating vs KMX's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Camping World Holdings, Inc. (CWH) and CarMax Inc (KMX) 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.

CWH currently trades at $7.66 with a QOC of 6.3/10, while KMX trades at $43.90 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).