LRMR vs LXRX

Larimar Therapeutics, Inc. vs Lexicon Pharmaceuticals, Inc. — Valuation Comparison 2026

LRMR

Pharmaceutical Preparations
Larimar Therapeutics, Inc.
Quality
4.8
out of 10
Value Trap
36
LOW
Price
$3.48
Last close
Models
7/13
Active
VS

LXRX

Pharmaceutical Preparations
Lexicon Pharmaceuticals, Inc.
Quality
7.4
out of 10
Value Trap
18
SAFE
Price
$2.18
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType LRMR Fair ValueLRMR Upside LXRX Fair ValueLXRX Upside
Bayesian DCF Intrinsic $1.86 -46.6% $0.59 -72.8%
Earnings Power Value Intrinsic $0.29 -81.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $1.82 -47.6% $0.18 -91.9%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

LRMR vs LXRX — Which Stock Is More Undervalued?

LXRX scores higher with a 7.4/10 quality rating vs LRMR's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Larimar Therapeutics, Inc. (LRMR) and Lexicon Pharmaceuticals, Inc. (LXRX) 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.

LRMR currently trades at $3.48 with a QOC of 4.8/10, while LXRX trades at $2.18 with a QOC of 7.4/10.

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).