Xpeng Inc. Surges 4.61% on $360M Volume, Ranks 318th in U.S. Trading

Xpeng Inc. (XPEV) surged 4.61% on Sept. 25, with a trading volume of $360 million, marking a 239.84% increase from the previous day and ranking 318th among U.S. stocks by volume. The rally followed strategic adjustments in its EV delivery model and renewed investor interest in the Chinese automaker’s cost-optimization initiatives.

Recent developments highlighted Xpeng’s shift to a more flexible delivery approach, including direct-to-consumer channels and partnerships with third-party dealerships. This strategy aims to reduce operational costs while expanding market reach in China’s competitive EV sector. Analysts noted the move could stabilize profit margins amid ongoing price wars in the industry.

Supply chain updates also contributed to the stock’s performance. Xpeng confirmed progress in securing lithium battery components from domestic suppliers, mitigating risks from global semiconductor shortages. The company’s focus on localized production aligns with broader industry trends to reduce dependency on overseas logistics.

To make sure I set up the back-test exactly the way you expect, I need to clarify a couple of points: 1. Universe selection • Do you want to use all U.S. common stocks (≈ 8,000 tickers) as the pool from which the “top-500-by-volume” list is drawn each day, or a narrower universe such as the Russell 3000 or S&P 500 constituents? 2. Portfolio construction • Should the 500 names be equally weighted each day (i.e., 0.20 % of capital in each), or do you prefer volume-weighted or other weighting? 3. Trading assumptions • Are you happy to ignore transaction costs and slippage, or would you like to include a per-trade cost assumption? 4. Tool capability • Our current back-testing engine handles one ticker at a time. To run a cross-sectional strategy like this, I can script an external workflow that: a) Pulls the full U.S. universe’s daily volume, b) Identifies the top-500 each day, c) Calculates the next-day equal-weighted portfolio return, and d) Aggregates the series into an equity curve. This is feasible, but please confirm you’re comfortable with me running a custom multi-asset workflow (it will take a bit longer to execute). Once I have your answers, I’ll build the data-retrieval plan and launch the back-test.