MSTR vs NCTY

Strategy Inc vs The9 Limited - American Deposit — Valuation Comparison 2026

MSTR

Finance Services
Strategy Inc
Quality
7.2
out of 10
Value Trap
45
WARN
Price
$159.09
Last close
Models
12/13
Active
VS

NCTY

Finance Services
The9 Limited - American Deposit
Quality
4.9
out of 10
Value Trap
18
SAFE
Price
$5.26
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType MSTR Fair ValueMSTR Upside NCTY Fair ValueNCTY Upside
Bayesian DCF Intrinsic $0.64 -87.9%
Earnings Power Value Intrinsic $37.70 -76.3%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $38.07 -76.1% $0.09 -98.4%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $302.47 +90.1% $0.46 -91.2%
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 MSTR vs NCTY — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MSTR vs NCTY — Which Stock Is More Undervalued?

MSTR scores higher with a 7.2/10 quality rating vs NCTY's 4.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Strategy Inc (MSTR) and The9 Limited - American Deposit (NCTY) 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.

MSTR currently trades at $159.09 with a QOC of 7.2/10, while NCTY trades at $5.26 with a QOC of 4.9/10.

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).