CSTE vs JBI

Caesarstone Ltd. vs Janus International Group, Inc. — Valuation Comparison 2026

CSTE

Building Products & Equipment
Caesarstone Ltd.
Quality
2.5
out of 10
Value Trap
Price
$1.82
Last close
Models
12/13
Active
VS

JBI

Building Products & Equipment
Janus International Group, Inc.
Quality
8.5
out of 10
Value Trap
17
SAFE
Price
$5.39
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType CSTE Fair ValueCSTE Upside JBI Fair ValueJBI Upside
Bayesian DCF Intrinsic $0.36 -80.2% $11.78 +118.6%
Earnings Power Value Intrinsic $0.93 -82.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $3.22 +76.7% $2.24 -58.5%
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 CSTE vs JBI — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CSTE vs JBI — Which Stock Is More Undervalued?

JBI scores higher with a 8.5/10 quality rating vs CSTE's 2.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Caesarstone Ltd. (CSTE) and Janus International Group, Inc. (JBI) 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.

CSTE currently trades at $1.82 with a QOC of 2.5/10, while JBI trades at $5.39 with a QOC of 8.5/10.

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).