PUK vs RGA

Prudential Public Limited Compa vs Reinsurance Group of America, I — Valuation Comparison 2026

PUK

Life Insurance
Prudential Public Limited Compa
Quality
1.7
out of 10
Value Trap
Price
$28.76
Last close
Models
13/13
Active
VS

RGA

Life Insurance
Reinsurance Group of America, I
Quality
6.6
out of 10
Value Trap
12
SAFE
Price
$200.74
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType PUK Fair ValuePUK Upside RGA Fair ValueRGA Upside
Bayesian DCF Intrinsic $10.35 -64.0% $872.10 +334.4%
Earnings Power Value Intrinsic $12.02 -60.9% $154.13 -23.2%
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 PUK vs RGA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PUK vs RGA — Which Stock Is More Undervalued?

RGA scores higher with a 6.6/10 quality rating vs PUK's 1.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Prudential Public Limited Compa (PUK) and Reinsurance Group of America, I (RGA) 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.

PUK currently trades at $28.76 with a QOC of 1.7/10, while RGA trades at $200.74 with a QOC of 6.6/10.

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).