AAP vs ADNT

Advance Auto Parts Inc. vs Adient plc — Valuation Comparison 2026

AAP

Auto Parts
Advance Auto Parts Inc.
Quality
6.6
out of 10
Value Trap
Price
$59.86
Last close
Models
12/13
Active
VS

ADNT

Auto Parts
Adient plc
Quality
7.4
out of 10
Value Trap
16
SAFE
Price
$23.74
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType AAP Fair ValueAAP Upside ADNT Fair ValueADNT Upside
Bayesian DCF Intrinsic $2.51 -95.8% $0.76 -96.8%
Earnings Power Value Intrinsic $35.49 -40.7% $38.11 +60.5%
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 AAP vs ADNT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

AAP vs ADNT — Which Stock Is More Undervalued?

ADNT scores higher with a 7.4/10 quality rating vs AAP's 6.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Advance Auto Parts Inc. (AAP) and Adient plc (ADNT) 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.

AAP currently trades at $59.86 with a QOC of 6.6/10, while ADNT trades at $23.74 with a QOC of 7.4/10.

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).