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Consumer Cyclical - Auto - Manufacturers - NASDAQ - CN
$ 27.37
-10.9 %
$ 28.5 B
Market Cap
20.73
P/E
1. INTRINSIC VALUE

This DCF valuation model was last updated on Mar, 3, 2025.

The intrinsic value of one LI stock under the worst case scenario is HIDDEN Compared to the current market price of 27.4 USD, Li Auto Inc. is HIDDEN

This DCF valuation model was last updated on Mar, 3, 2025.

The intrinsic value of one LI stock under the base case scenario is HIDDEN Compared to the current market price of 27.4 USD, Li Auto Inc. is HIDDEN

This DCF valuation model was last updated on Mar, 3, 2025.

The intrinsic value of one LI stock under the best case scenario is HIDDEN Compared to the current market price of 27.4 USD, Li Auto Inc. is HIDDEN

2. FUNDAMENTAL ANALYSIS
FINANCIALS
124 B REVENUE
173.48%
7.41 B OPERATING INCOME
302.66%
11.7 B NET INCOME
675.89%
50.7 B OPERATING CASH FLOW
586.88%
-12.1 M INVESTING CASH FLOW
99.72%
185 M FINANCING CASH FLOW
-96.71%
42.9 B REVENUE
35.34%
3.43 B OPERATING INCOME
633.43%
2.81 B NET INCOME
0.00%
11 B OPERATING CASH FLOW
2667.47%
-14.2 B INVESTING CASH FLOW
-270.19%
238 M FINANCING CASH FLOW
327.51%
Balance Sheet Li Auto Inc.
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Current Assets 115 B
Cash & Short-Term Investments 103 B
Receivables 144 M
Other Current Assets 11.1 B
Non-Current Assets 28.9 B
Long-Term Investments 1.6 B
PP&E 20.4 B
Other Non-Current Assets 6.91 B
Current Liabilities 72.7 B
Accounts Payable 34.8 B
Short-Term Debt 8.12 B
Other Current Liabilities 29.8 B
Non-Current Liabilities 10.1 B
Long-Term Debt 5.43 B
Other Non-Current Liabilities 4.72 B
EFFICIENCY
Earnings Waterfall Li Auto Inc.
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Revenue 124 B
Cost Of Revenue 96.4 B
Gross Profit 27.5 B
Operating Expenses 20.1 B
Operating Income 7.41 B
Other Expenses -4.3 B
Net Income 11.7 B
RATIOS
22.20% GROSS MARGIN
22.20%
5.98% OPERATING MARGIN
5.98%
9.45% NET MARGIN
9.45%
19.46% ROE
19.46%
8.16% ROA
8.16%
10.61% ROIC
10.61%
FREE CASH FLOW ANALYSIS
Free Cash Flow Analysis Li Auto Inc.
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Net Income 11.7 B
Depreciation & Amortization 1.81 B
Capital Expenditures -6.51 B
Stock-Based Compensation 2.38 B
Change in Working Capital 3.58 B
Others 36.1 B
Free Cash Flow 44.2 B
3. WALL STREET ANALYSTS ESTIMATES
Wall Street Analysts Price Targets Li Auto Inc.
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Wall Street analysts predict an average 1-year price target for LI of $41.1 , with forecasts ranging from a low of $15 to a high of $105 .
LI Lowest Price Target Wall Street Target
15 USD -45.20%
LI Average Price Target Wall Street Target
41.1 USD 50.21%
LI Highest Price Target Wall Street Target
105 USD 283.63%
4. DIVIDEND ANALYSIS
5. COMPETITION
6. Ownership
Insider Ownership Li Auto Inc.
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Sold
0-3 MONTHS
0 USD 0
3-6 MONTHS
0 USD 0
6-9 MONTHS
0 USD 0
9-12 MONTHS
0 USD 0
Bought
0 USD 0
0-3 MONTHS
0 USD 0
3-6 MONTHS
0 USD 0
6-9 MONTHS
0 USD 0
9-12 MONTHS
Date Value Insider Amount Avg Price
19 years ago
Dec 09, 2005
Sell 4.63 K USD
CARTY DOUGLAS A
Exec VP & CFO
- 211
21.95 USD
19 years ago
Nov 25, 2005
Sell 55 K USD
CARTY DOUGLAS A
Exec VP & CFO
- 2500
22 USD
7. News
BRDCY or LI: Which Is the Better Value Stock Right Now? Investors looking for stocks in the Automotive - Foreign sector might want to consider either Bridgestone Corp. (BRDCY) or Li Auto Inc. Sponsored ADR (LI). But which of these two stocks presents investors with the better value opportunity right now? zacks.com - 1 week ago
Brokers Suggest Investing in Li Auto (LI): Read This Before Placing a Bet When deciding whether to buy, sell, or hold a stock, investors often rely on analyst recommendations. Media reports about rating changes by these brokerage-firm-employed (or sell-side) analysts often influence a stock's price, but are they really important? zacks.com - 1 week ago
Chinese EV makers NIO, Xpeng, Li Auto see shares slip up to 6% after BYD's new partnership with DeepSeek NIO Inc.'s stock is trading lower on Tuesday following an announcement by BYD Auto regarding the inclusion of self-driving technology in its vehicles. The announcement is probably seen as a competitive challenge for NIO, as BYD's integration of advanced technology into more affordable models could pressure premium EV brands. invezz.com - 2 weeks ago
Why Li Auto Inc. Sponsored ADR (LI) Outpaced the Stock Market Today The latest trading day saw Li Auto Inc. Sponsored ADR (LI) settling at $26.37, representing a +1.35% change from its previous close. zacks.com - 3 weeks ago
Wall Street Bulls Look Optimistic About Li Auto (LI): Should You Buy? Investors often turn to recommendations made by Wall Street analysts before making a Buy, Sell, or Hold decision about a stock. While media reports about rating changes by these brokerage-firm employed (or sell-side) analysts often affect a stock's price, do they really matter? zacks.com - 4 weeks ago
Li Auto Inc. January 2025 Delivery Update BEIJING, China, Feb. 01, 2025 (GLOBE NEWSWIRE) -- Li Auto Inc. (“Li Auto” or the “Company”) (Nasdaq: LI; HKEX: 2015), a leader in China's new energy vehicle market, today announced that it delivered 29,927 vehicles in January 2025. As of January 31, 2025, Li Auto's cumulative deliveries reached 1,163,799. globenewswire.com - 1 month ago
Should You Buy Li Auto Stock While It's 50% Below Its All-Time High? Li Auto (LI 0.77%), a manufacturer of plug-in hybrid electric vehicles (PHEVs) and battery-powered electric vehicles (BEVs) in China, went public back in 2020. The stock rallied from its initial public offering price of $11.50 per ADS (American depositary share) to a record high of $46.65 in 2023. fool.com - 1 month ago
China and Global End-to-end Autonomous Driving Industry Report 2024-2025: How Li Auto Becomes a Leader from an Intelligent Driving Follower Dublin, Jan. 28, 2025 (GLOBE NEWSWIRE) -- The "End-to-end Autonomous Driving Industry Report, 2024-2025" report has been added to ResearchAndMarkets.com's offering. End-to-end intelligent driving research: How Li Auto becomes a leader from an intelligent driving follower There are two types of end-to-end autonomous driving: global (one-stage) and segmented (two-stage) types. The former has a clear concept, and much lower R&D cost than the latter, because it does not require any manually annotated data sets but relies on multimodal foundation models developed by Google, META, Alibaba and OpenAI. Standing on the shoulders of these technology giants, the performance of global end-to-end autonomous driving is much better than segmented end-to-end autonomous driving, but at extremely high deployment cost. Segmented end-to-end autonomous driving still uses the traditional CNN backbone network to extract features for perception, and adopts end-to-end path planning. Although its performance is not as good as global end-to-end autonomous driving, it has lower deployment cost. However, the deployment cost of segmented end-to-end autonomous driving is still very high compared with the current mainstream traditional "BEV+OCC+decision tree" solution. As a representative of global end-to-end autonomous driving, Waymo EMMA directly inputs videos without a backbone network but with a multimodal foundation model as the core. UniAD is a representative of segmented end-to-end autonomous driving. Based on whether feedback can be obtained, end-to-end autonomous driving researches are mainly divided into two categories: the research is conducted in simulators such as CARLA, and the next planned instructions can be actually performed; the research based on collected real data, mainly imitation learning, referring to UniAD. End-to-end autonomous driving currently features an open loop, so it is impossible to truly see the effects of the execution of one's own predicted instructions. Without feedback, the evaluation of open-loop autonomous driving is very limited. The two indicators commonly used in documents include L2 distance and collision rate. L2 distance: The L2 distance between the predicted trajectory and the true trajectory is calculated to judge the quality of the predicted trajectory. Collision rate: The probability of collision between the predicted trajectory and other objects is calculated to evaluate the safety of the predicted trajectory. The most attractive thing about end-to-end autonomous driving is the potential for performance improvement. The earliest end-to-end solution is UniAD. A paper at the end of 2022 revealed that the L2 distance was as long as 1.03 meters. It was greatly reduced to 0.55 meters at the end of 2023 and further to 0.22 meters in late 2024. Horizon Robotics is one of the most active companies in the end-to-end field, and its technology development also shows the overall evolution of the end-to-end route. After UniAD came out, Horizon Robotics immediately proposed VAD whose concept is similar to that of UniAD with much better performance. Then, Horizon Robotics turned to global end-to-end autonomous driving. Its first result was HE-Driver, which had a relatively large number of parameters. The following Senna has a smaller number of parameters and is also one of the best-performing end-to-end solutions. The core of some end-to-end systems is still BEVFormer which uses vehicle CAN bus information by default, including explicit information related to the vehicle's speed, acceleration and steering angle, exerting a significant impact on path planning. These end-to-end systems still require supervised training, so massive manual annotations are indispensable, which makes the data cost very high. Furthermore, since the concept of GPT is borrowed, why not use LLM directly, In this case, Li Auto proposed DriveVLM. The scenario description module of DriveVLM is composed of environment description and key object recognition. Environment description focuses on common driving environments such as weather and road conditions. Key object recognition is to find key objects that have a greater impact on current driving decision. Environment description includes the following four parts: weather, time, road type, and lane line. Differing from the traditional autonomous driving perception module that detects all objects, DriveVLM focuses on recognizing key objects in the current driving scenario that are most likely to affect autonomous driving decision, because detecting all objects will consume enormous computing power. Thanks to the pre-training of the massive autonomous driving data accumulated by Li Auto and the open source foundation model, VLM can better detect key long-tail objects, such as road debris or unusual animals, than traditional 3D object detectors. For each key object, DriveVLM will output its semantic category (c) and the corresponding 2D object box (b) respectively. Pre-training comes from the field of NLP foundation models, because NLP uses very little annotated data and is very expensive. Pre-training first uses massive unannotated data for training to find language structure features, and then takes prompts as labels to solve specific downstream tasks by fine-tuning. DriveVLM completely abandons the traditional algorithm BEVFormer as the core but adopts large multimodal models. Li Auto's DriveVLM leverages Alibaba's foundation model Qwen-VL with up to 9.7 billion parameters, 448*448 input resolution, and NVIDIA Orin for inference operations. How does Li Auto transform from a high-level intelligent driving follower into a leader? At the beginning of 2023, Li Auto was still a laggard in the NOA arena. It began to devote itself to R&D of high-level autonomous driving in 2023, accomplished multiple NOA version upgrades in 2024, and launched all-scenario autonomous driving from parking space to parking space in late November 2024, thus becoming a leader in mass production of high-level intelligent driving (NOA). Reviewing the development history of Li Auto's end-to-end intelligent driving, in addition to the data from its own hundreds of thousands of users, it also partnered with a number of partners on R&D of end-to-end models. DriveVLM is the result of the cooperation between Li Auto and Tsinghua University. In addition to DriveVLM, Li Auto also launched STR2 with Shanghai Qi Zhi Institute, Fudan University, etc., proposed DriveDreamer4D with GigaStudio, the Institute of Automation of Chinese Academy of Sciences, and unveiled MoE with Tsinghua University. Mixture of Experts (MoE) Architecture In order to solve the problem of too many parameters and too much calculation in foundation models, Li Auto has cooperated with Tsinghua University to adopt MoE Architecture. Mixture of Experts (MoE) is an integrated learning method that combines multiple specialized sub-models (i.e. 'experts') to form a complete model. Each 'expert' makes contributions in the field in which it is good at. The mechanism that determines which 'expert' participates in answering a specific question is called a 'gated network'. globenewswire.com - 1 month ago
Li Auto Inc. Sponsored ADR (LI) Exceeds Market Returns: Some Facts to Consider In the most recent trading session, Li Auto Inc. Sponsored ADR (LI) closed at $22.79, indicating a +0.75% shift from the previous trading day. zacks.com - 1 month ago
3 EV Stocks to Add in January, Before they Take Off in 2025 The electric vehicle transition has been something to behold, with market leaders such as Tesla (NASDAQ:TSLA) in the U.S. 247wallst.com - 1 month ago
Wall Street Analysts Think Li Auto (LI) Is a Good Investment: Is It? Investors often turn to recommendations made by Wall Street analysts before making a Buy, Sell, or Hold decision about a stock. While media reports about rating changes by these brokerage-firm employed (or sell-side) analysts often affect a stock's price, do they really matter? zacks.com - 1 month ago
US Listed Chinese Stocks Rally on Strong Trade Data, Central Bank Support, Goldman Forecasts 20% Growth US-listed Chinese stocks rise as China's 2024 trade hits $5.98T, with exports growing 7.1% and imports up 2.3%. benzinga.com - 1 month ago
8. Profile Summary

Li Auto Inc. LI

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COUNTRY CN
INDUSTRY Auto - Manufacturers
MARKET CAP $ 28.5 B
Dividend Yield 0.00%
Description Li Auto Inc. operates in the energy vehicle market in the People's Republic of China. It designs, develops, manufactures, and sells premium smart electric vehicles. The company's product line comprises MPVs and sport utility vehicles. It offers sales and after sales management, and technology development and corporate management services, as well as purchases manufacturing equipment. The company offers its products through online and offline channels. The company was formerly known as Leading Ideal Inc. and changed its name to Li Auto Inc. in July 2020. Li Auto Inc. was founded in 2015 and is headquartered in Beijing, the People's Republic of China.
Contact 11 Wenliang Street, Beijing, 101399 https://www.lixiang.com
IPO Date July 30, 2020
Employees 31591
Officers Mr. Liangjun Zou Senior Vice President Mr. Yang Wang Joint Company Secretary Mr. Tie Li Chief Financial Officer & Executive Director Mr. Yan Xie Senior Vice President & Chief Technology Officer Mr. Donghui Ma President & Executive Director Janet Chang Director of Investor Relations Ms. Yee Wa Lau Joint Company Secretary Mr. Xiang Li Founder, Executive Chairman & Chief Executive Officer Kobe Wang Head of Capital Markets