The Dow Jones Industrial Average (DJIA) lagged behind its major index peers on Friday, backsliding nearly 600 points at its lowest before staging a half-hearted recovery, trimming the day’s losses to around 250 points. The AI-focused tech sector is recovering from mid-week losses that continue to plague the steeply overinvested market segment. However, a recent bump in investment into the financial and building materials sectors is seeing a fresh drawdown as traders pile back into their preferred AI bets.
Overweight valuations remain a weak point in the ongoing AI tech rally. Cloud computing services providers and chip producers continue to be the winning shovel-sellers in the AI craze, and investors are beginning to grow leery of the increasingly circular AI space. Major market players spend most of their time writing out cheques for multi-billion dollar deals to invest in each other, and balance sheet wonks are getting increasingly agitated at how fast and loose many AI companies are being in how they classify spending investors’ money as “capex”.
With the longest US federal government shutdown ever now over, at least until the end of January, investors are waiting for word on when federal agencies will resume publishing official labor and inflation figures. Markets are expecting that September’s long-delayed Nonfarm Payrolls (NFP) jobs report will be released next week, however, some traders remain perplexed by the White House’s ambiguous warning that October’s jobs and inflation data may never be released at all.
Dow Jones daily chart
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.
Source: https://www.fxstreet.com/news/dow-jones-industrial-average-lags-behind-tech-sector-recovery-202511141803
