NEUP vs NKTR

Neuphoria Therapeutics Inc. vs Nektar Therapeutics — Valuation Comparison 2026

NEUP

Biotechnology
Neuphoria Therapeutics Inc.
Quality
5.4
out of 10
Value Trap
6
SAFE
Price
$5.36
Last close
Models
10/13
Active
VS

NKTR

Biotechnology
Nektar Therapeutics
Quality
5.9
out of 10
Value Trap
24
SAFE
Price
$65.01
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType NEUP Fair ValueNEUP Upside NKTR Fair ValueNKTR Upside
Bayesian DCF Intrinsic $3.75 -30.0% $18.82 -71.1%
Earnings Power Value Intrinsic $5.62 -93.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.61 -88.6% $0.22 -99.8%
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 NEUP vs NKTR — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NEUP vs NKTR — Which Stock Is More Undervalued?

NKTR scores higher with a 5.9/10 quality rating vs NEUP's 5.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Neuphoria Therapeutics Inc. (NEUP) and Nektar Therapeutics (NKTR) 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.

NEUP currently trades at $5.36 with a QOC of 5.4/10, while NKTR trades at $65.01 with a QOC of 5.9/10.

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).