FOXX vs LPL

Foxx Development Holdings Inc. vs LG Display Co, Ltd AMERICAN DEP — Valuation Comparison 2026

FOXX

Consumer Electronics
Foxx Development Holdings Inc.
Quality
5.5
out of 10
Value Trap
12
SAFE
Price
$2.76
Last close
Models
9/13
Active
VS

LPL

Consumer Electronics
LG Display Co, Ltd AMERICAN DEP
Quality
1.9
out of 10
Value Trap
Price
$5.03
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType FOXX Fair ValueFOXX Upside LPL Fair ValueLPL Upside
Bayesian DCF Intrinsic $0.62 -77.6% $1.48 -70.5%
Earnings Power Value Intrinsic $2.04 -58.4% $1.57 -62.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

FOXX vs LPL — Which Stock Is More Undervalued?

FOXX scores higher with a 5.5/10 quality rating vs LPL's 1.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Foxx Development Holdings Inc. (FOXX) and LG Display Co, Ltd AMERICAN DEP (LPL) 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.

FOXX currently trades at $2.76 with a QOC of 5.5/10, while LPL trades at $5.03 with a QOC of 1.9/10.

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).