TIPT vs UFCS

Tiptree Inc. vs United Fire Group, Inc — Valuation Comparison 2026

TIPT

Fire, Marine & Casualty Insurance
Tiptree Inc.
Quality
8.8
out of 10
Value Trap
28
LOW
Price
$18.24
Last close
Models
10/13
Active
VS

UFCS

Fire, Marine & Casualty Insurance
United Fire Group, Inc
Quality
9.2
out of 10
Value Trap
24
SAFE
Price
$44.33
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType TIPT Fair ValueTIPT Upside UFCS Fair ValueUFCS Upside
Bayesian DCF Intrinsic $65.93 +48.7%
Earnings Power Value Intrinsic $0.62 -96.5% $37.22 -16.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $9.51 -47.9% $100.74 +127.3%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 TIPT vs UFCS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

TIPT vs UFCS — Which Stock Is More Undervalued?

UFCS scores higher with a 9.2/10 quality rating vs TIPT's 8.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Tiptree Inc. (TIPT) and United Fire Group, Inc (UFCS) 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.

TIPT currently trades at $18.24 with a QOC of 8.8/10, while UFCS trades at $44.33 with a QOC of 9.2/10.

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).