UPC vs VERA

Universe Pharmaceuticals Inc vs Vera Therapeutics, Inc. — Valuation Comparison 2026

UPC

Pharmaceutical Preparations
Universe Pharmaceuticals Inc
Quality
1.5
out of 10
Value Trap
15
SAFE
Price
$3.50
Last close
Models
4/13
Active
VS

VERA

Pharmaceutical Preparations
Vera Therapeutics, Inc.
Quality
4.6
out of 10
Value Trap
24
SAFE
Price
$35.52
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType UPC Fair ValueUPC Upside VERA Fair ValueVERA Upside
Bayesian DCF Intrinsic $0.53 -84.7% $10.77 -69.7%
Earnings Power Value Intrinsic $15.75 -58.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $9.06 +235.7%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for UPC vs VERA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

UPC vs VERA — Which Stock Is More Undervalued?

VERA scores higher with a 4.6/10 quality rating vs UPC's 1.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Universe Pharmaceuticals Inc (UPC) and Vera Therapeutics, Inc. (VERA) 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.

UPC currently trades at $3.50 with a QOC of 1.5/10, while VERA trades at $35.52 with a QOC of 4.6/10.

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).