EVR vs FUFU

Evercore Inc. vs BitFuFu Inc. — Valuation Comparison 2026

EVR

Capital Markets
Evercore Inc.
Quality
9.0
out of 10
Value Trap
14
SAFE
Price
$346.92
Last close
Models
13/13
Active
VS

FUFU

Capital Markets
BitFuFu Inc.
Quality
7.0
out of 10
Value Trap
20
SAFE
Price
$2.00
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType EVR Fair ValueEVR Upside FUFU Fair ValueFUFU Upside
Bayesian DCF Intrinsic $532.66 +53.5% $0.20 -89.8%
Earnings Power Value Intrinsic $147.70 -57.4% $0.10 -94.8%
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 EVR vs FUFU — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EVR vs FUFU — Which Stock Is More Undervalued?

EVR scores higher with a 9.0/10 quality rating vs FUFU's 7.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Evercore Inc. (EVR) and BitFuFu Inc. (FUFU) 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.

EVR currently trades at $346.92 with a QOC of 9.0/10, while FUFU trades at $2.00 with a QOC of 7.0/10.

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).