AlphaStocks

LI vs PAYC

As of Sep 20, 2026, Li Auto (LI) scores 1.5/10 and Paycom Software (PAYC) 7.7/10 on AlphaStocks' five-model composite, so PAYC scores higher. PAYC trades 11% below its model fair value.

LI

Li Auto Inc.

1.5

Avoid

$12.14

PAYC

Paycom Software, Inc.

7.7

Strong Buy

$226.36

LI vs PAYC: Which is the Better Investment?

Li Auto Inc. (LI) scores 1.5/10 while Paycom Software, Inc. (PAYC) scores 7.7/10 on AlphaStocks' composite model. Paycom Software, Inc. has the higher composite rating of Strong Buy. On a P/E basis, Li Auto Inc. trades at 23.1x, making it the more attractively priced of the two.

This comparison is algorithmically generated and is not financial advice.

MetricLIPAYC
Scores & Fundamentals
Composite Score1.5/107.7/10
RatingAvoidStrong Buy
Price$12.14$226.36
P/E Ratio23.128.0
ROE1.6%20.5%
Market Cap$26B$12B
Fair Value$255.07
Dividend Yield1.1%
Sector Rank#253 of 265#4 of 265
Model Verdicts
PiotroskiCautionAttractive
BuffettCautionStrong
GrahamNeutralNeutral
LynchLimited DataStrong
GreenblattCautionAttractive
View full LIanalysis →View full PAYCanalysis →

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LI vs PAYC: Which Stock Scores Higher?

Li Auto Inc. (LI) and Paycom Software, Inc. (PAYC) are both in the Industrials sector. PAYC currently leads with a composite score of 7.7/10 (Strong Buy) compared to LI's 1.5/10 (Avoid).

The AlphaStocks composite score evaluates each stock across four dimensions: Quality (business strength measured by Piotroski F-Score and Buffett quality criteria), Value (discount to intrinsic worth using Graham, Lynch, and Greenblatt models), Momentum (6-month price trend), and Timing (a confirmation signal that requires both value and momentum to align). A higher composite score indicates stronger overall fundamentals combined with favorable market conditions.

This comparison uses the same scoring framework for both companies, ensuring an apples-to-apples evaluation. Scores are recalculated daily after market close using data from SEC filings and market prices. Read the full methodology to understand how each model contributes to the composite score.

Scores are algorithm-generated research tools, not investment recommendations. Past performance does not guarantee future results. Always do your own due diligence. Full disclaimer