CTSH vs EPAM

Cognizant Technology Solutions vs EPAM Systems, Inc. — Valuation Comparison 2026

CTSH

Information Technology Services
Cognizant Technology Solutions
Quality
8.8
out of 10
Value Trap
17
SAFE
Price
$53.85
Last close
Models
13/13
Active
VS

EPAM

Information Technology Services
EPAM Systems, Inc.
Quality
9.0
out of 10
Value Trap
27
LOW
Price
$101.43
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType CTSH Fair ValueCTSH Upside EPAM Fair ValueEPAM Upside
Bayesian DCF Intrinsic $81.58 +51.5% $203.95 +101.1%
Earnings Power Value Intrinsic $51.88 -3.7% $94.38 -7.0%
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 CTSH vs EPAM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CTSH vs EPAM — Which Stock Is More Undervalued?

EPAM scores higher with a 9.0/10 quality rating vs CTSH's 8.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Cognizant Technology Solutions (CTSH) and EPAM Systems, Inc. (EPAM) 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.

CTSH currently trades at $53.85 with a QOC of 8.8/10, while EPAM trades at $101.43 with a QOC of 9.0/10.

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).