GDYN vs GLOB

Grid Dynamics Holdings, Inc. vs Globant S.A. — Valuation Comparison 2026

GDYN

Information Technology Services
Grid Dynamics Holdings, Inc.
Quality
8.2
out of 10
Value Trap
25
LOW
Price
$7.37
Last close
Models
12/13
Active
VS

GLOB

Information Technology Services
Globant S.A.
Quality
7.8
out of 10
Value Trap
25
LOW
Price
$39.93
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType GDYN Fair ValueGDYN Upside GLOB Fair ValueGLOB Upside
Bayesian DCF Intrinsic $8.40 +13.9% $67.13 +68.1%
Earnings Power Value Intrinsic $4.64 -37.1% $23.54 -41.0%
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 GDYN vs GLOB — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

GDYN vs GLOB — Which Stock Is More Undervalued?

GDYN scores higher with a 8.2/10 quality rating vs GLOB's 7.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Grid Dynamics Holdings, Inc. (GDYN) and Globant S.A. (GLOB) 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.

GDYN currently trades at $7.37 with a QOC of 8.2/10, while GLOB trades at $39.93 with a QOC of 7.8/10.

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).