Asian Stocks struggle as OpenAI revenue miss hits AI sector, trade concerns loom
- Asian stocks declined as weakness in tech shares following lower-than-reported OpenAI revenue dragged down regional AI leaders.
- Mainland Chinese markets fell amid caution over EU-China trade negotiations, while Hong Kong’s Hang Seng posted a late gain.
- Retreating crude oil prices offered temporary relief against inflation fears, though elevated US Treasury yields restricted market upside.
Asian stocks struggled on Friday following an overnight selloff in US tech shares, as concerns over OpenAI’s revenue outlook weighed heavily on the broader artificial intelligence sector. Market sentiment took a hit after reports revealed that OpenAI’s annualized revenue stood at $50 billion at the end of September, falling short of the $68 billion figure widely reported the previous month.
Investors, particularly in Japan, are increasingly questioning whether AI-related revenue can justify the massive capital expenditure in the sector, especially given Japanese firms' critical role in building global AI infrastructure. Consequently, Japan's Nikkei 225 recovered from an initial bearish gap to trade down slightly by 0.13% around 68,950, dragged lower by AI-linked heavies like Advantest, Kioxia Holdings, and SoftBank Group. Despite Friday's drag, the index managed to secure its fourth consecutive weekly gain.
In mainland China, broader caution surrounding international trade further dampened market appetite. The Shanghai Composite dropped 1.2% to 3,765, while the Shenzhen Component slid 2.1% to a multi-month low of 12,480 as investors closely monitored the conclusion of China-EU trade talks. European industry groups pressed for immediate action against unfair Chinese commercial practices, warning of impending threats to EU manufacturing and employment. These negotiations capped three months of tense deliberations over the EU's massive goods trade deficit with China, alongside Beijing’s stringent restrictions on exports of rare earths and critical minerals.
Bucking the regional downtrend, Hong Kong’s Hang Seng Index rose 1.1% to 24,050, putting it on track to break a two-week losing streak as bargain hunters stepped in to buy beaten-down stocks. Regional sentiment saw late-session support as US index futures advanced and Asian markets bounced off their lows.
Furthermore, crude oil prices pulled back after US President Donald Trump stated he would refrain from military action against Iran before the November midterm elections. While the drop in energy costs helped alleviate immediate inflation anxieties, persistently high US Treasury yields continued to cast a shadow over the broader market outlook.
US equity rally narrows as ai narrative shows signs of strain
Analysts at Rabobank argue that “relative valuations may be playing a role” in the latest pullback, noting that US equity indices have retreated from record highs even as gains remain heavily concentrated in a small cohort of tech leaders. They highlight that “US equity market breadth is remarkably narrow, with AI-adjacent tech megacaps leading indices higher in recent times as many other sectors struggle for traction,” underscoring the increasingly lopsided nature of the rally. The bank adds that “the AI narrative had a wobble yesterday as SpaceX 5-year CDS spreads widened by 16.5bps to 197bps,” a move they see as emblematic of growing investor caution around the risk profile of high-profile AI-linked names.
AI stocks FAQs
First and foremost, artificial intelligence is an academic discipline that seeks to recreate the cognitive functions, logical understanding, perceptions and pattern recognition of humans in machines. Often abbreviated as AI, artificial intelligence has a number of sub-fields including artificial neural networks, machine learning or predictive analytics, symbolic reasoning, deep learning, natural language processing, speech recognition, image recognition and expert systems. The end goal of the entire field is the creation of artificial general intelligence or AGI. This means producing a machine that can solve arbitrary problems that it has not been trained to solve.
There are a number of different use cases for artificial intelligence. The most well-known of them are generative AI platforms that use training on large language models (LLMs) to answer text-based queries. These include ChatGPT and Google’s Bard platform. Midjourney is a program that generates original images based on user-created text. Other forms of AI utilize probabilistic techniques to determine a quality or perception of an entity, like Upstart’s lending platform, which uses an AI-enhanced credit rating system to determine credit worthiness of applicants by scouring the internet for data related to their career, wealth profile and relationships. Other types of AI use large databases from scientific studies to generate new ideas for possible pharmaceuticals to be tested in laboratories. YouTube, Spotify, Facebook and other content aggregators use AI applications to suggest personalized content to users by collecting and organizing data on their viewing habits.
Nvidia (NVDA) is a semiconductor company that builds both the AI-focused computer chips and some of the platforms that AI engineers use to build their applications. Many proponents view Nvidia as the pick-and-shovel play for the AI revolution since it builds the tools needed to carry out further applications of artificial intelligence. Palantir Technologies (PLTR) is a “big data” analytics company. It has large contracts with the US intelligence community, which uses its Gotham platform to sift through data and determine intelligence leads and inform on pattern recognition. Its Foundry product is used by major corporations to track employee and customer data for use in predictive analytics and discovering anomalies. Microsoft (MSFT) has a large stake in ChatGPT creator OpenAI, the latter of which has not gone public. Microsoft has integrated OpenAI’s technology with its Bing search engine.
Following the introduction of ChatGPT to the general public in late 2022, many stocks associated with AI began to rally. Nvidia for instance advanced well over 200% in the six months following the release. Immediately, pundits on Wall Street began to wonder whether the market was being consumed by another tech bubble. Famous investor Stanley Druckenmiller, who has held major investments in both Palantir and Nvidia, said that bubbles never last just six months. He said that if the excitement over AI did become a bubble, then the extreme valuations would last at least two and a half years or long like the DotCom bubble in the late 1990s. At the midpoint of 2023, the best guess is that the market is not in a bubble, at least for now. Yes, Nvidia traded at 27 times forward sales at that time, but analysts were predicting extremely high revenue growth for years to come. At the height of the DotCom bubble, the NASDAQ 100 traded for 60 times earnings, but in mid-2023 the index traded at 25 times earnings.
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