REZI vs SITE

Resideo Technologies, Inc. vs SiteOne Landscape Supply, Inc. — Valuation Comparison 2026

REZI

Industrial Distribution
Resideo Technologies, Inc.
Quality
7.5
out of 10
Value Trap
23
SAFE
Price
$31.34
Last close
Models
11/13
Active
VS

SITE

Industrial Distribution
SiteOne Landscape Supply, Inc.
Quality
9.3
out of 10
Value Trap
39
LOW
Price
$111.72
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType REZI Fair ValueREZI Upside SITE Fair ValueSITE Upside
Bayesian DCF Intrinsic $74.20 -33.6%
Earnings Power Value Intrinsic $12.01 -61.7% $15.97 -85.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $7.14 -82.6% $48.58 -56.5%
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 REZI vs SITE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

REZI vs SITE — Which Stock Is More Undervalued?

SITE scores higher with a 9.3/10 quality rating vs REZI's 7.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Resideo Technologies, Inc. (REZI) and SiteOne Landscape Supply, Inc. (SITE) 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.

REZI currently trades at $31.34 with a QOC of 7.5/10, while SITE trades at $111.72 with a QOC of 9.3/10.

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).