Top rated stocks today

The 20 highest-scoring stocks on the DeepVane APEX engine right now. Scores are a composite of 13 academic factor families — quality, value, momentum, insider flow, and 9 more — with Bayesian regime-conditional weighting. Updated daily at 06:00 UTC. Not investment advice.

#TickerSectorScoreVerdictChange
1
TROW
T. Rowe Price Group
Financial Services84mixed+1.9%
2
BKNG
Booking Holdings
Consumer81bullish+0.4%
3
ADBE
Adobe Inc.
Technology80bullish-2.1%
4
NU
Nu Holdings
Financials79bullish+1.6%
5
SPCE
Virgin Galactic
Industrials78bullish+8.4%
6
AAP
Advance Auto Parts
Consumer Cyclical78bullish+2.0%
7
LUNR
Intuitive Machines
Industrials78bullish+6.2%
8
H
Hyatt Hotels
Consumer Cyclical78bullish+4.5%
9
RMD
ResMed Inc.
Healthcare78bullish+0.9%
10
IONQ
IonQ Inc.
Technology78bullish+9.5%
11
CLSK
CleanSpark Inc.
Technology77mixed+8.1%
12
DVA
DaVita Inc.
Healthcare77bullish+23.6%
13
ASTS
AST SpaceMobile
Communication Services77bullish+10.7%
14
IART
Integra LifeSciences
Healthcare76bullish+5.9%
15
SCHW
Charles Schwab
Financials76bullish-0.3%
16
ICE
Intercontinental Exchange
Financials76mixed-1.2%
17
NFLX
Netflix Inc.
Communication76bullish+0.4%
18
HLT
Hilton Worldwide
Consumer76bullish+2.8%
19
RDW
Redwire Corporation
Industrials75bullish+10.9%
20
MP
MP Materials
Basic Materials75bullish+6.7%

Lowest rated stocks

Stocks with the weakest APEX composite signal. Low score does not mean "sell" — it means the academic factors are currently unfavorable.

1
MPWRMonolithic Power Systems
Semiconductors71bullish
2
CBChubb Limited
Financial Services71mixed
3
ITWIllinois Tool Works
Industrials71bullish
4
LRCXLam Research
Semiconductors71bullish
5
PGProcter & Gamble
Consumer71mixed
6
KMBKimberly-Clark
Consumer71bullish
7
RIVNRivian Automotive
Consumer Cyclical72bullish
8
AEMAgnico Eagle Mines
Basic Materials72bullish
9
CUZCousins Properties
Real Estate72bullish
10
GDGeneral Dynamics
Industrials72bullish

How the APEX score works

Every day at 06:00 UTC, DeepVane scores 1000+ publicly traded stocks across 13 peer-reviewed academic factor families: quality (Novy-Marx 2013), value (Fama-French 1992), momentum (Jegadeesh-Titman 1993), insider flow (Seyhun 1998), post-earnings drift (Bernard-Thomas 1989), accruals quality (Sloan 1996), NLP tone (Loughran-McDonald 2011), options positioning (Pan-Poteshman 2006), sector momentum (Moskowitz-Grinblatt 1999), industry spillover (Cohen-Frazzini 2008), short interest (Asquith-Pathak-Ritter 2005), microstructure (Amihud 2002), and factor interaction (Asness-Moskowitz-Pedersen 2013).

Factors are blended using Bayesian regime-conditional weights — the engine detects whether the market is in an expansion, contraction, or transition phase and adjusts how much weight each factor receives accordingly. Each score comes with a Mondrian conformal prediction interval showing how certain the model is about its call.

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