ONC vs ORIC

BeOne Medicines Ltd. vs Oric Pharmaceuticals, Inc. — Valuation Comparison 2026

ONC

Biotechnology
BeOne Medicines Ltd.
Quality
9.7
out of 10
Value Trap
6
SAFE
Price
$290.58
Last close
Models
13/13
Active
VS

ORIC

Biotechnology
Oric Pharmaceuticals, Inc.
Quality
4.7
out of 10
Value Trap
18
SAFE
Price
$8.45
Last close
Models
7/13
Active

Model-by-Model Comparison

ModelType ONC Fair ValueONC Upside ORIC Fair ValueORIC Upside
Bayesian DCF Intrinsic $179.01 -38.4% $2.50 -70.4%
Earnings Power Value Intrinsic $67.55 -76.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $54.94 -81.1% $3.62 -57.1%
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 ONC vs ORIC — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ONC vs ORIC — Which Stock Is More Undervalued?

ONC scores higher with a 9.7/10 quality rating vs ORIC's 4.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing BeOne Medicines Ltd. (ONC) and Oric Pharmaceuticals, Inc. (ORIC) 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.

ONC currently trades at $290.58 with a QOC of 9.7/10, while ORIC trades at $8.45 with a QOC of 4.7/10.

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).