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24 minutes ago
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XPeng, NIO, Li Auto, ZEEKR Post Big July Delivery Gains, Yet Stocks Remain Under Pressure
Chinese electric vehicle (EV) makers XPeng (NYSE:XPEV), ZEEKR Intelligent Technology (NYSE:ZK), Li Auto (NASDAQ:LI), and NIO (NYSE:NIO) stocks dropped on Friday despite individual triumphs like XPeng's record July deliveries and ZEEKR's significant year-over-year growth. ZEEKR, a subsidiary of Geely, announced on Friday that its combined Zeekr and Lynk & Co brands delivered 44,193 vehicles in July 2025, marking a 19.7% increase from the prior year. Specifically, the Zeekr brand contributed 16,977 deliveries, while Lynk & Co accounted for 27,216 units. The company had previously unveiled its Super Hybrid Technologies on July 9, built on its new full-stack SEA-S platform. This innovative system features a 900V high-voltage architecture, tri-silicon carbide-powered e-motors, and a CATL Freevoy Super Hybrid plans to integrate this technology into its forthcoming Zeekr 9X, which boasts a peak output of 1,030kW and an impressive 0 to 100 km/h acceleration in under 3.1 seconds. Li Auto reported 30,731 vehicle deliveries in July 2025, bringing its cumulative deliveries to 1,368,541 units by the end of the month. The company also officially launched the Li i8, a six-seat battery-electric family SUV, on July 29, with customer deliveries anticipated to commence on August 20. Li Auto's expanding footprint includes 535 retail stores across 153 cities, 527 servicing centers, and authorized body and paint shops in 222 cities, complemented by 3,028 supercharging stations with 16,671 charging stalls throughout China. NIO also released its July 2025 delivery figures on Friday, reporting a total of 21,017 vehicles. This total comprised 12,675 vehicles from its premium smart EV brand NIO, 5,976 from its family-oriented ONVO brand, and 2,366 from its small high-end EV brand FIREFLY. Cumulative deliveries for NIO reached 806,731 vehicles by July 31, 2025. The company officially launched the ONVO L90, a smart flagship SUV, on July 31, with user deliveries expected to begin shortly. XPeng, which reported its July 2025 delivery results on Thursday, achieved a new monthly record with 36,717 Smart EV deliveries, marking an astounding 229% year-over-year increase. This represents the ninth consecutive month of deliveries exceeding 30,000 units. As of July 2025, XPeng's cumulative deliveries surpassed 800,000 units, with 233,906 Smart EVs delivered from January to July 2025, a 270% year-over-year surge. The company is actively expanding its global presence, having launched the 2025 XPeng G6 and G9 versions in European markets in mid-July, alongside plans to introduce the XPeng P7+ in Europe. The widespread stock market underperformance across the Chinese EV sector signals mounting investor apprehension, exacerbated by intensifying margin pressure stemming from fierce domestic price wars and considerable geopolitical headwinds. Price Action: At last check Friday, NIO's stock had dipped 2.26%, trading at $4.77 per share, while Li Auto saw a 3.83% drop premarket. XPeng, despite impressive growth, was down 1.7%, and ZEEKR's stock fell by 1.02%. Photo by Robert Way via Shutterstock UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? NIO (NIO): Free Stock Analysis Report This article XPeng, NIO, Li Auto, ZEEKR Post Big July Delivery Gains, Yet Stocks Remain Under Pressure originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved. Error while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data
Yahoo
28 minutes ago
- Yahoo
5 questions Trump faces after dismal jobs report; BLS commissioner firing
President Trump's economic pitch took a serious hit Friday after the latest federal jobs report revealed stunning weakness in the labor market. He responded by firing the commissioner of the Bureau of Labor Statistics (BLS) for what he called politically motivated revisions that lobbed off hundreds of thousands of job gains earlier this summer. The dismal jobs report raised serious questions about the strength of the U.S. economy, especially in light of looming tariffs causing anxieties in the global market. Here are the five big questions facing Trump as he faces the fallout. How much worse does it get? After months of warnings from economists and weakening data from the private sector, federal jobs numbers have caught up to the concern. The July jobs report dramatically changed the picture of the U.S. economy, ramping up concerns fueled by Trump's tariffs and the uncertainty they unleashed. The U.S. added only 73,000 jobs in July and just 106,000 jobs since May — a three-month total barely enough to sustain the labor market for one month. 'Not only was this a much weaker than forecast payrolls number, the monster downward revisions to the past two months inflicts a major blow to the picture of labor market robustness,' Seema Shah, chief global strategist at Principal Asset Management, wrote in an analysis. 'More concerning is that with the negative impact of tariffs only just starting to be felt, the coming months are likely to see even clearer evidence of a labor market slowdown.' The U.S. economy needs to add 80,000 to 100,000 jobs each month just to replace those who leave the workforce for retirement or incapacity. Without a significant turnaround, the unemployment rate could begin to rise, and the overall economy could slow drastically. 'The U.S. slowdown is starting to take shape,' Alexandra Wilson-Elizondo, global co-chief investment officer at Goldman Sachs Asset Management, wrote in a Friday analysis. She added that a decline in labor force participation, which is also bad for the job market, was keeping the unemployment rate from rising further. 'While overall levels are not flashing red, the trend is cause for concern,' she wrote. How does Trump adjust his tariff plans? Trump and top White House officials spent months laughing off the dire projections of economists, who feared his tariffs would tank the job market and boost inflation. That position may not be tenable after Friday. The July jobs report came out on what was supposed to be the final deadline for the imposition of Trump's 'reciprocal' tariffs. After insisting for weeks that he would not delay the deadline further, Trump announced Thursday evening that some countries would have an additional week to strike deals with the U.S. Trump's latest punt — which happened after the president is typically briefed on the jobs report — was the latest in a series of delays issued amid rough economic news or stock market turmoil. The president proposed much steeper tariffs during his 'Liberation Day' announcement in April, but he delayed and weakened his plan after two weeks of turmoil in financial markets. Trump and top White House economic aides touted the benefit of federal revenue from import taxes, which are paid by the U.S. businesses and individuals who purchase foreign goods. But the growing pressure of his tariffs could prompt further delays from Trump. Trump could also keep higher headline tariff rates while quietly making exemptions for key goods, undermining the overall goal of his import taxes while potentially avoiding some of the costs. 'A web of exemptions and, in the case of the deals, preferential rates means many key imports face lower tariffs or none. That significantly lowers the actual tariff rate, in many cases well below the quoted headline rate,' Michael Pearce, deputy chief U.S. economist at Oxford Economics, wrote in a Friday analysis. How does the Fed respond? The stunning July jobs numbers will boost pressure on the Federal Reserve to cut interest rates at its next policy meeting in September and are raising questions about whether it should have cut rates already. The Fed kept rates steady Wednesday as inflation continued to rise and the labor market appeared to be weakening at a much slower rate than seen in Friday's jobs report. While Fed Chair Jerome Powell acknowledged Wednesday the risks that the job market could weaken quicker than expected under the bank's moderately high interest rates, he said he and his colleagues were still unsettled about how Trump's tariffs could drive inflation higher. The Fed now appears to be in a quagmire with the country on track for both a weaker economy and higher inflation — a dynamic known as 'stagflation.' Lower interest rates could stimulate the sluggish labor market but also drive inflation higher with additional money in the economy. Keeping interest rates unchanged could stave off inflation but suffocate the economy into higher unemployment and slower spending. 'With persistent policy uncertainty, tariffs, and diminished immigration flows paralyzing employers, the U.S. economy is now flirting with job losses, revealing a labor market that is much weaker than most Fed policymakers had believed,' Gregory Daco, chief economist EY-Parthenon, wrote in a Friday analysis. 'The Fed is now behind the curve.' Will voters ding Trump as job approval sinks? Trump is largely fulfilling his campaign promises on the economy, including instituting tariffs, though that policy proved to be much more widespread than what he suggested while running for a second term. He's also making good on mass deportation plans, which the administration is using to sell what they see as a stronger economy for the American worker. But some slices of voters don't appear to be singing Trump's praises. Trump headed into the big week on the economy with his job approval rating slipping, with net approval dropping 15 points, according to an Economist/YouGov poll. And his net approval rating also fell 9 points to its lowest rating yet last week in the Decision Desk HQ average, with independents taking issue with Trump's actions on the economy and immigration. Consumer confidence ticked up only slightly in July, a sign that anxieties over the economy could be coming to a head as a result of the president's policies. Consumers also expressed more negative assessments of their economic situations overall. What impact will firing the BLS commissioner have? Experts and economists were left reeling Friday afternoon when Trump announced he was firing the Commissioner of Bureau of Labor Statistics Erika McEntarfer. That cast doubt on the bureau's reporting standards and the type of revisions it makes on previously released reports. When Trump was later asked if that decision meant anyone providing him data he doesn't agree with could risk losing their job, he responded: 'I've always had a problem with these numbers.' In considering who could be McEntarfer's long-term replacement, Trump did not pinpoint experience in labor statistics as a qualification. 'We need people we can trust,' Trump said. 'I put somebody in who's going to be honest.' Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed. Solve the daily Crossword
Yahoo
29 minutes ago
- Yahoo
‘Artificial stupidity' made AI trading bots spontaneously form cartels when left unsupervised, Wharton study reveals
A study from University of Pennsylvania's Wharton School and the Hong Kong University of Science and Technology found that when placed in simulated markets, AI trading bots did not compete with one another, but rather began colluding in price-fixing behaviors. According to the study authors, research on how AI behaves in market environments can help regulators understand gaps in existing rules and statutes. Artificial intelligence is just smart—and stupid—enough to pervasively form price-fixing cartels in financial market conditions if left to their own devices. A working paper posted this month on the National Bureau of Economic Research website from the Wharton School at the University of Pennsylvania and Hong Kong University of Science and Technology found when AI-powered trading agents were released into simulated markets, the bots colluded with one another, engaging in price fixing to make a collective profit. In the study, researchers let bots loose in market models, essentially a computer program designed to simulate real market conditions and train AI to interpret market-pricing data, with virtual market makers setting prices based on different variables in the model. These markets can have various levels of 'noise,' referring to the amount of conflicting information and price fluctuation in the various market contexts. While some bots were trained to behave like retail investors and others like hedge funds, in many cases, the machines engaged in 'pervasive' price-fixing behaviors by collectively refusing to trade aggressively—without being explicitly told to do so. In one algorithmic model looking at price-trigger strategy, AI agents traded conservatively on signals until a large enough market swing triggered them to trade very aggressively. The bots, trained through reinforcement learning, were sophisticated enough to implicitly understand that widespread aggressive trading could create more market volatility. In another model, AI bots had over-pruned biases and were trained to internalize that if any risky trade led to a negative outcome, they should not pursue that strategy again. The bots traded conservatively in a 'dogmatic' manner, even when more aggressive trades were seen as more profitable, collectively acting in a way the study called 'artificial stupidity.' 'In both mechanisms, they basically converge to this pattern where they are not acting aggressively, and in the long run, it's good for them,' study co-author and Wharton finance professor Itay Goldstein told Fortune. Financial regulators have long worked to address anti-competitive practices like collusion and price fixing in markets. But in retail, AI has taken the spotlight, particularly as legislators call on companies to address algorithmic pricing. For example, Sen. Ruben Gallego (D-Ariz.) called Delta's practice of using AI to set individual airfare prices 'predatory pricing,' though the airline previously told Fortune its fares are 'publicly filed and based solely on trip-related factors.' 'For the [Securities and Exchange Commission] and those regulators in financial markets, their primary goal is to not only preserve this kind of stability, but also ensure competitiveness of the market and market efficiency,' Winston Wei Dou, Wharton professor of finance and one of the study's authors, told Fortune. With that in mind, Dou and two colleagues set out to identify how AI would behave in a financial market by putting trading agent bots into various simulated markets based on high or low levels of 'noise.' The bots ultimately earned 'supra-competitive profits' by collectively and spontaneously deciding to avoid aggressive trading behaviors. 'They just believed sub-optimal trading behavior as optimal,' Dou said. 'But it turns out, if all the machines in the environment are trading in a 'sub-optimal' way, actually everyone can make profits because they don't want to take advantage of each other.' Simply put, the bots didn't question their conservative trading behaviors because they were all making money and therefore stopped engaging in competitive behaviors with one another, forming de-facto cartels. Fears of AI in financial services With the ability to increase consumer inclusion in financial markets and save investors time and money on advisory services, AI tools for financial services, like trading agent bots, have become increasingly appealing. Nearly one third of U.S. investors said they felt comfortable accepting financial planning advice from a generative AI-powered tool, according to a 2023 survey from financial planning nonprofit CFP Board. A report last week from cryptocurrency exchange MEXC found that among 78,000 Gen Z users, 67% of those traders activated at least one AI-powered trading bot in the previous fiscal quarter. But for all their benefits, AI trading agents aren't without risks, according to Michael Clements, director of financial markets and community at the Government Accountability Office (GAO). Beyond cybersecurity concerns and potentially biased decision-making, these trading bots can have a real impact on markets. 'A lot of AI models are trained on the same data,' Clements told Fortune. 'If there is consolidation within AI so there's only a few major providers of these platforms, you could get herding behavior—that large numbers of individuals and entities are buying at the same time or selling at the same time, which can cause some price dislocations.' Jonathan Hall, an external official on the Bank of England's Financial Policy Committee, warned last year of AI bots encouraging this 'herd-like behavior' that could weaken the resilience of markets. He advocated for a 'kill switch' for the technology, as well as increased human oversight. Exposing regulatory gaps Clements explained many financial regulators have so far been able to apply well-established rules and statutes to AI, saying for example, 'Whether a lending decision is made with AI or with a paper and pencil, rules still apply equally.' Some agencies, such as the SEC, are even opting to fight fire with fire, developing AI tools to detect anomalous trading behaviors. 'On the one hand, you might have an environment where AI is causing anomalous trading,' Clements said. 'On the other hand, you would have the regulators in a little better position to be able to detect it as well.' According to Dou and Goldstein, regulators have expressed interest in their research, which the authors said has helped expose gaps in current regulation around AI in financial services. When regulators have previously looked for instances of collusion, they've looked for evidence of communication between individuals, with the belief that humans can't really sustain price-fixing behaviors unless they're corresponding with one another. But in Dou and Goldstein's study, the bots had no explicit forms of communication. 'With the machines, when you have reinforcement learning algorithms, it really doesn't apply, because they're clearly not communicating or coordinating,' Goldstein said. 'We coded them and programmed them, and we know exactly what's going into the code, and there is nothing there that is talking explicitly about collusion. Yet they learn over time that this is the way to move forward.' The differences in how human and bot traders communicate behind the scenes is one of the 'most fundamental issues' where regulators can learn to adapt to rapidly developing AI technologies, Goldstein argued. 'If you use it to think about collusion as emerging as a result of communication and coordination,' he said, 'this is clearly not the way to think about it when you're dealing with algorithms.' This story was originally featured on Error while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data
