RBLX vs TTWO

Roblox Corporation vs Take-Two Interactive Software, — Valuation Comparison 2026

RBLX

Electronic Gaming & Multimedia
Roblox Corporation
Quality
4.4
out of 10
Value Trap
36
LOW
Price
$46.83
Last close
Models
12/13
Active
VS

TTWO

Electronic Gaming & Multimedia
Take-Two Interactive Software,
Quality
8.1
out of 10
Value Trap
25
LOW
Price
$217.87
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType RBLX Fair ValueRBLX Upside TTWO Fair ValueTTWO Upside
Bayesian DCF Intrinsic $16.08 -65.7% $12.75 -94.1%
Earnings Power Value Intrinsic $26.36 -53.0% $229.13 -3.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
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 RBLX vs TTWO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

RBLX vs TTWO — Which Stock Is More Undervalued?

TTWO scores higher with a 8.1/10 quality rating vs RBLX's 4.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Roblox Corporation (RBLX) and Take-Two Interactive Software, (TTWO) 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.

RBLX currently trades at $46.83 with a QOC of 4.4/10, while TTWO trades at $217.87 with a QOC of 8.1/10.

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).