ACHC vs AIRS

Acadia Healthcare Company, Inc. vs AirSculpt Technologies, Inc. — Valuation Comparison 2026

ACHC

Medical Care Facilities
Acadia Healthcare Company, Inc.
Quality
6.1
out of 10
Value Trap
12
SAFE
Price
$23.20
Last close
Models
9/13
Active
VS

AIRS

Medical Care Facilities
AirSculpt Technologies, Inc.
Quality
5.9
out of 10
Value Trap
21
SAFE
Price
$5.38
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType ACHC Fair ValueACHC Upside AIRS Fair ValueAIRS Upside
Bayesian DCF Intrinsic $0.37 -93.2%
Earnings Power Value Intrinsic $0.17 -94.9%
EROIC Spread Intrinsic $90.55 +290.3%
First Chicago Scenario $19.98 -13.2% $1.64 -69.6%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 ACHC vs AIRS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ACHC vs AIRS — Which Stock Is More Undervalued?

ACHC scores higher with a 6.1/10 quality rating vs AIRS's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Acadia Healthcare Company, Inc. (ACHC) and AirSculpt Technologies, Inc. (AIRS) 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.

ACHC currently trades at $23.20 with a QOC of 6.1/10, while AIRS trades at $5.38 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).