Quick Summary
Covering the latest research from top Wall Street investment banks

Post-holiday China EV orders broadly rolled back, and model cycles widened OEM divergence

Institution
Morgan Stanley
Date
2026-05-12
Authors
Stanley Wang, Peggy Wang, Shelley Wang, CFA
Company
-
Ticker
-
Industry
Auto Manufacturers; EV; China Autos & Shared Mobility
Rating
Asia Pacific Industry View: In-Line
NeutralLow confidenceThe report notes a broad post-holiday decline in China EV weekly orders similar to last year, but highlights sharp OEM divergence driven by model cycles; the disclosed Asia Pacific industry view is In-Line.
AuthorsStanley Wang, Peggy Wang, Shelley Wang, CFA
CoverageAsia-Pacific
Asset classesEquity
Business segmentsElectric vehicles、Autos、Shared mobility
Research firm divisions/subsidiariesMorgan Stanley(Other)、Morgan Stanley Asia Limited(Other)

AI summary card

Post-holiday China EV orders broadly rolled back, and model cycles widened OEM divergence

Morgan Stanley weekly channel feedback shows that from May 4 to 6, after the holiday, weekly orders for major new-energy automakers mostly fell on a sequential basis, while Tesla China, Li Auto and NIO were relatively more resilient, and attention has shifted to flagship SUV launches in May.

Industry view is In-Line; in the stock coverage table, Geely Automobile Holdings, NIO Inc., XPeng Inc. and several other EV-related stocks are rated Overweight.
China autosNew-energy vehiclesWeekly ordersModel cyclesHong Kong/U.S. auto stocks
  • The post-holiday weekly order decline trend was broadly similar to last year, but the magnitude of decline across OEMs was clearly different, mainly driven by model-cycle factors.
  • Tesla China orders were about 12.0-12.2k, with week-on-week +9% and year-on-year +33%, showing relatively strong performance in the sample.
  • XPeng orders were about 6.4-6.6k, with week-on-week -21% and year-on-year -12%, with market focus on L03/L05.
  • Geely Galaxy orders were about 18.9-19.4k, with week-on-week -46% and year-on-year -21%, reverting to normal after the peak following the M7.
  • Xiaomi orders were about 7.5-7.7k, with week-on-week -44% and year-on-year +24%, with SU7 contributing 65-70% of the inflow.

Report interpretation

Overview

This report is Morgan Stanley’s Asia Pacific/China electric-vehicle weekly order industry tracking. The core conclusion is that after the extended holiday, major EV manufacturers saw orders decline sharply, with overall rhythm similar to last year, but order resilience differed significantly across automakers, and model cycles are the main explanatory factor. The report also notes that a dense rollout of flagship SUVs in the remaining period of May will become the investment focus.

Core views

The report argues that the post-holiday sales decline itself is not surprising; the key is the differences in decline magnitude and model-pace among different OEMs. Tesla China, Li Auto and NIO were relatively more resilient because they had a lower comparison base and lacked new-model noise; Geely Galaxy, HIMA/Aito and Xiaomi showed more pronounced pullback after earlier model and brand traffic peaks; XPeng declined week-on-week but market focus remains on new models such as L03/L05.

Analysis framework

The report is based on channel-feedback statistics for major Chinese EV brands’ weekly orders during May 4-6, and uses week-on-week, month-over-month and year-on-year changes to measure post-holiday order strength, then combines new model launches, flagship SUV release cadence and prior high base to explain OEM divergence.

Methodology notes

  • Industry high-frequency trackingWeekly channel order tracking

    Track short-cycle order changes through channel feedback

    This approach uses weekly order ranges with WoW, MoM and YoY changes to quickly gauge demand momentum, but the data come from channel feedback and are suitable for tracking trends and dispersion, not equivalent to final deliveries or financial revenue.

  • Cycle analysisModel-cycle analysis

    Use new-model launches and prior model high base to explain order changes

    The report attributes order divergence mainly to model cycles, including expectations for new flagship SUV launches, order peaks from earlier hit models, and relative resilience when there is less disturbance from new models.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

  • Geely Automobile Holdings / Geely Galaxy (0175.HK)
    China EV order-tracking sample; in the disclosed coverage table, Geely Automobile Holdings is rated Overweight.
    Strengths
    Orders remain at a scale of 18.9-19.4k, with MoM at +10%.
    Weaknesses
    WoW -46% and YoY -21%, showing a pronounced post-holiday pullback from the prior high.
    Comparison
    Compared with Tesla China and Leapmotor, Geely Galaxy has a larger week-on-week decline.
    Risks
    If normalization after the post-M7 peak happens too quickly, it may affect the market’s view of short-term demand persistence.
  • XPeng Inc. (9868.HK/XPEV.N)
    A key EV manufacturer; the disclosed coverage table rates XPeng Inc. as Overweight.
    Strengths
    Market focus on L03/L05, and the next model cycle could become a catalyst.
    Weaknesses
    Orders of 6.4-6.6k, with WoW -21%, MoM -40%, YoY -12%.
    Comparison
    The week-on-week decline is smaller than that of Geely Galaxy, HIMA/Aito and Xiaomi, but YoY remains negative.
    Risks
    If attention on new models does not convert into orders, valuation and growth expectations may come under pressure.
  • Tesla China
    A major competitor in the China EV market and a demand barometer.
    Strengths
    Orders of 12.0-12.2k, with WoW +9%, MoM +12%, YoY +33%, showing notably strong resilience.
    Weaknesses
    The report does not provide more granular model mix or pricing strategy information.
    Comparison
    Within the disclosed sample, Tesla China is one of the few brands with positive week-on-week growth.
    Risks
    Increased competition, pricing shifts, or changes in model-refresh cadence could affect order sustainability.
  • Xiaomi (1810.HK)
    A consumer-electronics and smart-vehicle-related name newly entering EV business.
    Strengths
    Orders of 7.5-7.7k, YoY +24%, with SU7 contributing 65-70% of order inflow.
    Weaknesses
    WoW -44% and MoM -20%, indicating a clear post-holiday pullback.
    Comparison
    Order momentum is weaker than Tesla China in the short term, but still shows YoY growth.
    Risks
    Orders are heavily dependent on SU7 inflows; model supply, delivery cadence and demand persistence need close monitoring.
  • NIO Inc. (9866.HK/NIO.N)
    A China EV manufacturer; the main text states NIO’s order trend is relatively resilient, and NIO Inc. is rated Overweight in the coverage table.
    Strengths
    The report states that its post-holiday weekly orders are relatively more resilient.
    Weaknesses
    The main text does not disclose a specific weekly order range.
    Comparison
    NIO is grouped with Tesla China and Li Auto as players with comparatively stronger resilience.
    Risks
    Lack of detailed weekly order data in this report means follow-up disclosures or channel updates are needed for validation.

Key data

  • Geely Galaxy (0175.HK) weekly orders18.9-19.4kWoW -46%, MoM +10%, YoY -21%; returned to normal from the order peak after M7.
  • XPeng (9868.HK/XPEV.N) weekly orders6.4-6.6kWoW -21%, MoM -40%, YoY -12%; market focus on L03/L05.
  • Leapmotor weekly orders18.4-18.6kWoW -23%, MoM +48%, YoY +67%.
  • Tesla China weekly orders12.0-12.2kWoW +9%, MoM +12%, YoY +33%; relatively more resilient than most automakers.
  • HIMA weekly orders11.1-11.3kWoW -52%, MoM +45%.
  • Aito weekly orders7.0-7.2kWoW -51%, MoM +41%, YoY -43%.
  • Xiaomi (1810.HK) weekly orders7.5-7.7kWoW -44%, MoM -20%, YoY +24%; SU7 accounted for 65-70% of order inflow.

Impact & implications

For investors, in the short term, one should not focus only on post-holiday week-on-week order pullback; it is important to assess whether the pullback exceeds seasonal patterns, which brands can maintain resilience at low bases or during new-car windows, and whether May flagship SUV launches can deliver incremental orders. At the industry level, model cycles and product cadence remain the main drivers of relative performance among China EV shares.

Risks

  • Channel-feedback data may differ from final deliveries, retail sales, or financial revenue.
  • Post-holiday order pullbacks may include both seasonal effects and genuine demand weakening and should be tracked continuously.
  • Model cycles have a large impact on orders; new-model launch pace, acceptance and delivery execution can alter short-term trends.
  • The report discloses that Morgan Stanley has investment banking, shareholding, or other potential business ties with several covered companies; investors should note conflict-of-interest disclosures.
  • U.S. executive orders, export controls and jurisdictional regulatory limits may affect eligibility for trading certain securities or investing.

What to watch

  • Flagship SUV launches and order conversion over the remaining period of May.
  • Whether the relative order resilience of Tesla China, Li Auto and NIO can be sustained.
  • Subsequent order inflow changes for XPeng’s L03/L05, Geely-related models and Xiaomi’s SU7.
  • Whether the post-holiday week-on-week order decline reverts to normal seasonal levels in coming weeks.
  • The validation relationship between weekly orders and subsequent monthly sales and delivery volumes.
Zhejiang ICP No. 2022035445-5
Disclaimer: Market data, charts, indicators, research views, and other information provided on this website are intended solely for information display, research communication, and educational reference. They should not be regarded as personalized investment advice, securities recommendations, trading instructions, solicitations, or guarantees of return. While we strive to improve the reliability of our data and content, such information may still be subject to delays, errors, incompleteness, or untimely updates due to source differences, methodological limitations, system processing, or market volatility. Users should exercise independent judgment based on their own circumstances and bear all risks and responsibilities arising from the use of this website.

Settings

Sign in to view recent logins