Reddit, the 19-year-old website that hosts millions of online forums, priced its IPO on Wednesday at $34 a share, the top of the expected range.
The offering brought in $519 million, according to a press release, and values the company at close to $6.5 billion. Reddit had planned to price the deal at $31 to $34 a share.
Reddit’s public market debut on Thursday, under ticker symbol “RDDT,” will be the first for a major social media company since Pinterest’s debut in 2019 and one of the very few venture-backed tech deals of the past two years. Reddit sold 15.28 million shares in the offering, while existing shareholders sold another 6.72 million.
The company is taking a haircut from its private market valuation of $10 billion in 2021 at the peak of the tech boom. Soaring inflation and rising interest rates pushed investors out of risky assets in 2022, eventually forcing startups to downsize, slash their valuations and focus on profit over growth.
On Wednesday, data center hardware company Astera Labs went public, and saw its shares skyrocket 72%, as investors flock to anything involving artificial intelligence. However, the IPO market has been in an extended dry spell for more than two years, with Instacart, Klaviyo and Arm Holdings among the few tech companies to hold offerings over that stretch.
Reddit’s core business of online advertising faces competition from industry giants like Alphabet and Meta. The company also counts Snap, X, Pinterest, Discord, Wikipedia and Amazon’s Twitch streaming service as competitors, according to its prospectus.
Revenue increased 20% last year to $804 from $666.7 million in 2022. Its net loss in 2023 was $90.8 million, marking an improvement from the $158.6 million net loss it recorded the previous year.
The company has said in filings that data licensing could become a big money maker, and that it plans to recognize about $66.4 million in such deals in 2024. The company recently entered an expanded partnership with Google, allowing the search giant more access to Reddit data to train AI models and other tasks.
Last week, Reddit said the Federal Trade Commission sent a letter to the company inquiring about its data-licensing practices.
As part of the initial public offering, Redditgave some of its leading moderators and users, known as Redditors, a chance to buy stock through a directed-share program. It’s a model that was previously used by Airbnb, Doximity and Rivian to reward their power users and customers.
This illustration picture taken on April 20, 2018 in Paris shows apps for Google, Amazon, Facebook, Apple (GAFA) and the reflexion of a binary code displayed on a tablet screen. (Photo by Lionel BONAVENTURE / AFP) (Photo credit should read LIONEL BONAVENTURE/AFP via Getty Images)
Lionel Bonaventure | Afp | Getty Images
Apple is reportedly in talks with Google to let the iPhone maker license and build its Gemini artificial intelligence engine into the iPhone, according to a Bloomberg report.
Gemini is Google’s suite of generative AI tools, which ranges from chatbots to coding assistants.
Bloomberg, citing people familiar with the matter, said that the two tech giants are “in active negotiations” for Gemini to power certain new features due to be released to the iPhone software later in the year.
Apple could launch the iOS 18 — its latest operating system for the iPhone — at its Worldwide Developer’s Conference in June.
Apple also recently held discussions with OpenAI and has considered using its model, according to the people cited by Bloomberg.
However, the report said “the two parties haven’t decided the terms or branding of an AI agreement or finalized how it would be implemented.”
Apple and Google did not immediately respond to CNBC’s request for comment.
Reddit said Friday that the Federal Trade Commission sent a letter to the company about its data-licensing business related to the training of artificial intelligence systems.
“On March 14, 2024, we received a letter from the FTC advising us that the FTC’s staff is conducting a non-public inquiry focused on our sale, licensing, or sharing of user-generated content with third parties to train AI models,” Reddit said in an updated IPO prospectus. Reddit filed for an IPO in February, and plans to trade on the New York Stock Exchange under the ticker symbol “RDDT.”
Although Reddit’s core business relies on online advertising, the company is seeking to make money in other ways, and is in the “early stages” of its “data licensing efforts,” the filing said.
Reddit said “the opportunity does not conflict with our values and the rights of our Redditors,” referring to its users and forum moderators.
The 19-year-old company has filed to sell shares in its IPO at $31 to $34 each in an offering that would value the business at close to $6.5 billion. Reddit is trying to hit the public market during a historically slow period for tech IPOs. There hasn’t been a notable venture-backed tech debut since Instacart and Klaviyo in September. And before that the market had been largely shuttered since late 2021.
Reddit’s revenue rose 20% last year to $804 million. About 98% of its sales came from advertising. The remaining 2% includes data licensing.
“These programs may subject us to evolving approaches to the regulation of this data and implicates complex and developing data privacy and data protection, misappropriation, and intellectual property laws, rules, and regulations,” Reddit said in the updated filing.
An FTC spokesperson declined to comment.
Reddit said it entered into some data-licensing deals in January with a total contract value of $203 million over two to three years. It expects to recognize at least $66.4 million from these agreements in 2024.
The same week that Reddit filed for its IPO, Googleannounced an expanded partnership with the company, giving the search giant access to data to train its AI models, among other uses.
“We believe our growing platform data will be a key element in the training of leading large language models (“LLMs”) and serve as an additional monetization channel for Reddit,” the company said in its prospectus.
Reddit said it’s “not surprised that the FTC has expressed interest” in the matter, considering “the novel nature of these technologies and commercial arrangements.”
“We do not believe that we have engaged in any unfair or deceptive trade practice,” Reddit said. “The letter indicated that the FTC staff was interested in meeting with us to learn more about our plans and that the FTC intended to request information and documents from us as its inquiry continues.”
Reddit noted that any dealings with regulators could be “lengthy and unpredictable” and could result in “substantial costs” and other probes and product changes that could “require us to change our policies or practices, divert management and other resources from our business, or otherwise adversely impact our business, results of operations, financial condition, and prospects.”
Reddit’s data-licensing business was at the center of a widespread protest from Reddit moderators, who were upset over the summer when the company announced a pricing change impacting some third-party developers using its application programming interface, or API, to build apps.
The company said at the time that the API price hike was necessary to ensure that it was adequately compensated by tech companies like Google and OpenAI, which siphon massive amounts of Reddit data to help train and improve the capabilities of their AI models. But several developers complained that the API update proved too costly for them to continue operating their Reddit apps, which some Redditors used to help them moderate discussions.
Children: A son born in 2009 and another child born in 2011
Education: University of Michigan, B.S.E., 1995; Stanford University, M.S., 1998
Google is a play on the word googol, the term for the numeral one followed by 100 zeroes.
Page has a vocal cord condition that he says is responsible for his hoarser, softer speaking voice. He also has Hashimoto’s thyroiditis, a disorder that causes inflammation of the thyroid gland.
2010 – Kittyhawk, a flying car company, is founded by Sebastian Thrun with the backing of Page. On September 21, 2022, Kittyhawk announces that it plans to “wind down” operations.
April 4, 2011-October 2, 2015 – CEO of Google.
August 10, 2015 – Google announces a corporate restructuring, forming an umbrella company called Alphabet and naming Sundar Pichai as the new CEO to the core business of Google. Page will serve as Alphabet’s CEO and Brin will serve as president.
August 2021 – New Zealand government officials confirm that Page is a New Zealand resident following news that Page entered the country during border restrictions due to Covid-19. According to immigration officials, Page applied for residency in November 2020.
OpenAI CEO Sam Altman addresses a speech during a meeting, at the Station F in Paris on May 26, 2023.
Joel Saget | AFP | Getty Images
Tech firms and Silicon Valley billionaires have been pouring money into nuclear energy for years, pitching the sustainable power source as crucial to the green transition. Now they have another incentive to promote it: artificial intelligence.
While generative AI has grown at lightning speed, nuclear power projects are heavily regulated and usually advance at a plodding pace. That’s raising questions about whether advances in nuclear energy can cut emissions as swiftly as energy-guzzling AI and other fast-growing technologies are adding to them.
“If you were to integrate large language models, GPT-style models into search engines, it’s going to cost five times as much environmentally as standard search,” said Sarah Myers West, managing director of the AI Now Institute, a research group focused on the social impacts of AI. At current growth rates, some new AI servers could soon gobble up more than 85 terawatt hours of electricity each year, researchers have estimated — more than some small nations’ annual energy consumption.
“I want to see innovation in this country,” Myers West said. “I just want the scope of innovation to be determined beyond the incentive structures of these giant companies.”
Oklo is one of the nuclear startups backed by Sam Altman, the CEO of OpenAI who has described AI and cheap, green energy as mutually reinforcing essentials to achieving a future marked by “abundance.”
“Fundamentally today in the world, the two limiting commodities you see everywhere are intelligence, which we’re trying to work on with AI, and energy,” he told CNBC in 2021 after investing $375 million in Helion Energy, a nuclear fusion startup that Altman chairs. Microsoft last year agreed to buy power from Helion starting in 2028. Oklo, which Altman also chairs, is focused on the opposite reaction, fission, which generates energy by splitting an atom; fusion does so by merging atomic nuclei.
Representatives for Altman, through his special acquisition company AltC, didn’t respond to a request for comment.
In rural southeastern Idaho, Oklo is working to build a small-scale nuclear powerhouse that could fuel data centers like the ones OpenAI and its competitors need. But the company also wants to supply mixed-use communities and industrial facilities, and is already contracted to build two commercial plants in southern Ohio.
As the United States moves toward wide-scale electric vehicle adoption and decarbonization, “the amount of energy we’re going to need to do that is huge,” said Oklo CEO and co-founder Jacob DeWitte. “Also heating and cooking — if we want to electrify those processes, you’re going to need even more.”
Oklo has found getting regulators on board harder than finding potential customers.
In 2022, the federal Nuclear Regulatory Commission, which oversees commercial nuclear power plants and materials, denied the company’s application for the design of its Idaho “Aurora” powerhouse, saying it hadn’t provided enough safety information. In October, the Air Force rescinded its intent to award a contract for a microreactor pilot program to power a base in Alaska.
“You’ve got new physics, you have to use new models. You have to do all sorts of stuff that’s different than what they’re used to,” DeWitte said of the NRC. Oklo is now working to satisfy regulators, he said, acknowledging agency officials must “do their independent job of ensuring this meets adequate safety requirements.”
Oklo’s proposed 13,000 square-foot Aurora powerhouse, featuring a 15-megawatt fission reactor, is smaller than earlier plants and looks more like a sleek ski chalet than the Cold War-era ones with their iconic curved towers. The plant set to be built at the Idaho National Laboratory, a research facility where Oklo has been given an Energy Department grant to test recycling nuclear waste into new fuel. DeWitte says the design is safer, too, citing the use of liquid metal as a coolant rather than water.
The nuclear power industry hasn’t meaningfully expanded its share of the U.S. energy mix for decades. It has chugged along despite popular opposition fueled by infrequent but devastating accidents like those in Chernobyl, Ukraine, in 1986 and in Fukushima, Japan, in 2011. But as the climate crisis accelerates, most Americans now support expanding nuclear energy — 57%, up from 43% in 2020, a Pew Research survey found last year.
Nuclear power currently makes up only 19% of the nation’s overall energy generation, with 93 commercial reactors operating today, down from a peak of 112 in 1990. By one estimate, up to 800 gigawatts of new nuclear power will be needed by 2050 to meet current green energy targets.
Unit 3’s reactor and cooling tower stand at Georgia Power Co.’s Plant Vogtle nuclear power plant on Jan. 20, 2023, in Waynesboro, Ga.
John Bazemore | AP
But as tech firms sprint toward AI, many data centers are already struggling to add capacity fast enough to remain affordable, with data center rents jumping nearly 16% between 2022 and last year alone. The demand crunch is one reason major industry players have been ramping up their nuclear investments.
Microsoft signed a deal last summer with Constellation, a top nuclear power plant operator, to add nuclear-generated electricity to its Virginia data centers. The year before, Google took part in a $250 million fundraising round for the fusion startup TAE Technologies. And in late 2021, Amazon founder Jeff Bezos and other investors raised over $130 million for Canadian nuclear company General Fusion.
For tech firms, it makes sense to tap directly into nuclear plants “instead of sourcing electricity from the grid,” said Ross Matzkin-Bridger, a senior director at the Nuclear Threat Initiative, a nonprofit group focused on reducing nuclear and biological risks. In addition to being clean, he noted, many recent nuclear projects are also compact. “You can fit a lot more energy per acre in nuclear energy than you can with any other technology,” he said.
Beyond Silicon Valley, “big investment firms are actually starting to believe that this is going to take off,” said Ayan Paul, a research scientist at Northeastern University who studies AI. “People have started to believe that these kinds of energies are going to fuel our population.”
But some experts warn that efforts to expand nuclear power shouldn’t be rushed, no matter how fast demand is growing.
“We need nuclear power to get to a low-carbon future,” said Ahmed Abdulla, assistant mechanical and aerospace engineering professor at Carleton University. But for engineering projects that have historically taken decades, the regulatory process needs to be a methodical one, he said: “There is a chance to make serious mistakes if we sprint to the goal.”
British digital bank Monzo on Tuesday raised $430 million in fresh capital from investors to help it relaunch its services in the U.S.
Monzo raised the money in a new funding round led by CapitalG, the independent venture arm of Google parent company Alphabet.
HongShan, the Chinese venture capital firm that split from Sequoia Capital last year, also backed the round, alongside existing backers Tencent and Passion Capital.
Monzo, which is one of the U.K.’s most popular app-only banks, said the fresh cash would be used to accelerate its expansion plans. The bank’s CEO, TS Anil, told the Financial Times the capital would allow Monzo to crack the U.S. market after its previous foray was curtailed by U.S. regulators.
“With backing from global investors, we have the rocket fuel to go after our ambitions harder and faster, building Monzo into the one app that sits at the centre of our customers’ financial lives,” Monzo CEO TS Anil said in a statement.
“Each milestone we’ve reached to this point has given us more strength and speed to make strides towards our mission — now we’ll scale to even greater heights and seize the huge opportunity ahead.”
The fresh cash comes off the back of bumper growth for Monzo in 2023.
The U.K. neobank entered the black for the first time in the first two months of 2023. That came as Monzo reported 88% growth in revenues to £214.5 million ($272 million), up from £114 million in 2022.
A fair portion of the cash will be allocated toward helping Monzo relaunch its services in the U.S.
Monzo previously tried launching in the U.S. in 2019, with a beta product available for American consumers. The company was live in the U.S. via a partnership with the community bank Sutton Bank.
It wanted to acquire a full U.S. bank license, but it was forced to abandon this plan in 2021 after a fruitless two-year discourse with regulatory authorities.
Monzo has since opted to focus on re-entering the U.S. with a partnership that would allow it to bypass the requirement of getting a full bank license to serve U.S. customers.
The firm began a search for a U.S. CEO in 2023 to spearhead a renewed attempt at cracking the American market. It hired Conor Walsh, a former executive at fintech firm Block’s Cash App division, as its new U.S. CEO in October 2023.
Monzo’s new round also comes after a focus on new products for the bank. Monzo made its first foray into investment products in 2023, launching investment pots that allow customers to park their cash at a range of funds managed by BlackRock with different levels of risk.
Monzo said it now has more than 9 million retail customers in the U.K., and that it added 2 million of those clients in 2023 alone. The company also has 400,000 business banking customers.
Sam Altman, CEO of OpenAI, at the Hope Global Forums annual meeting in Atlanta on Dec. 11, 2023.
Dustin Chambers | Bloomberg | Getty Images
OpenAI executives disputed claims Elon Musk laid out in a lawsuit on Thursday, and said the Tesla CEO is upset that he’s no longer part of the artificial intelligence startup.
“We believe the claims in this suit may stem from Elon’s regrets about not being involved with the company today,” wrote OpenAI Chief Strategy Officer Jason Kwon in an internal memo on Friday that was viewed by CNBC. “It is deeply disappointing to see Elon take this action against a company he helped start, especially given his close collaboration with some of you who are still here working towards the mission.”
Musk co-founded OpenAI in 2015 and stepped down from its board in 2018, four years after saying that AI is “potentially more dangerous than nukes.”
Musk is now suing Microsoft–backed OpenAI and CEO Sam Altman, among others, alleging they abandoned the company’s founding mission to develop artificial intelligence “for the benefit of humanity broadly.”
Since releasing the ChatGPT chatbot to the public in late 2022, OpenAI has become one of the hottest startups on the planet, with a valuation reportedly over $80 billion. The company’s convoluted “capped-profit” structure resulted in Altman being briefly ousted by the board late last year, before an uproar among investors and employees led to his quick reinstatement.
Musk has long wanted recognition for his central role in the creation of OpenAI, and he spent large chunks of the lawsuit telling his version of events. His lawyers said in the suit that Musk was approached in 2015 by Altman and OpenAI co-founder Greg Brockman and agreed to form a nonprofit lab that would develop artificial general intelligence, or AGI, outside of the corporate sphere.
Musk’s attorneys said their client contributed over $15 million to OpenAI in 2016, which was “more than any other donor” and helped the startup build a team of “top talent.” The next year, Musk gave nearly $20 million to OpenAI, which the attorneys reiterated was more than other backers. In total, Musk invested over $44 million into OpenAI from 2016 through September 2020, according to the suit.
Additionally, Musk leased OpenAI’s initial office space “and paid the monthly rental expenses,” the suit said. He was also “present for important company milestones.”
Kwon didn’t dispute Musk’s central role in the early days of OpenAI, but he added some other details. For example, Kwon wrote that Musk at one point indicated he needed “full initial control and majority equity” and later suggested that OpenAI merge with Tesla.
“We did not think either approach was right for the mission,” Kwon wrote.
In the memo, Altman called Musk a hero of his and said the he misses the old version of his co-founder. But he said the company’s mission continues.
While it’s the first time the dispute between the two sides has resulted in a fiery lawsuit, they’ve been at odds for a while.
Before he split with OpenAI, Tesla hired co-founder Andrej Karpathy as senior director of AI. Karpathy returned to OpenAI in 2023. And Musk has been notably vocal in his opposition to OpenAI and its Microsoft partnership in recent years, stating publicly in November that OpenAI had deviated from its original mission.
“OpenAI should be renamed ‘super closed source for maximum profit AI,’ because this is what it actually is,” Musk said onstage at The New York Times’ DealBook conference. Regarding OpenAI’s transformation from an “open source foundation” to a multibillion-dollar for-profit company, Musk said, “I don’t know, is this legal?”
Kwon insisted on Friday that OpenAI is independent and continues to work “to ensure AGI benefits all of humanity.”
Musk’s lawyers didn’t immediately respond to a request for comment.
— CNBC’s Lora Kolodny and Hayden Field contributed to this report
Passengers ride in an electric Waymo full self-driving technology in Santa Monica
Allen J. Schaben | Los Angeles Times | Getty Images
Alphabet’s Waymo robotaxi unit won approval from the California Public Utilities Commission to expand service to parts of Los Angeles and the Bay Area, according to a notice posted to the regulator’s website on Friday.
“Waymo may begin fared driverless passenger service operations in the specified areas of Los Angeles and the San Francisco Peninsula, effective today,” the release said.
In mid-February, Waymo initiated a voluntary recall filing notice with the National Highway Traffic Safety Administration, saying it would fix software issues. The recall followed two previously undisclosed incidents that occurred in Phoenix on Dec. 11, in which unmanned Waymo vehicles crashed into the same towed pickup truck within minutes of each other.
The collisions added to existing concerns about autonomous vehicle use in California. Competing taxi and transit service providers and labor activists are worried about the loss of drivers’ jobs, while safety advocates wrote letters to regulators and politicians asking them to thwart Waymo’s expansion in the state.
The CPUC in February had suspended Waymo’s expansion efforts for up to 120 days to provide for added review time.
In its letter on Friday, the regulator said it was approving the new proposal, due in part to “Waymo’s updated Passenger Safety Plan (PSP), submitted in connection with its expanded operational design domain (ODD) for deployment,” which was also approved by the California Department of Motor Vehicles.
“We’re grateful to the CPUC for this vote of confidence in our operations, which paves the way for the deployment of our commercial Waymo One service in Los Angeles and the San Francisco Peninsula,” a Waymo spokesperson said in a statement.
Waymo’s progress in California comes after General Motors-owned Cruise and Apple bowed out of the autonomous vehicle business in California, while Elon Musk’s Tesla has yet to develop an autonomous vehicle that can safely operate without a human driver at the controls.
California regulators halted operations of self-driving Cruise robotaxis in October after a series of incidents, including one that resulted in a robotaxi rolling over a pedestrian who had first been hit by a human-driven car and was then pulled forward about 20 feet by the Cruise vehicle.
Waymo’s new approvals allow the company’s robotaxis to operate close to Tesla’s Palo Alto engineering headquarters in San Mateo County.
The latest notice applies to the commercial ride-sharing service Waymo One. The company has deployed testing vehicles in those areas for several years.
You, too, can have your own RCS chat with Google Gemini. Image: Google
Android is becoming the platform of AI fever dreams. At this year’s MWC, an overseas tradeshow where Google typically has a booth to remind the world that its mobile platform is global, the Android maker has announced new ways to interact with Gemini from inside Google Messages as if Gemini were just another buddy.
No Google AI Search, I Don’t Need to Learn About the “Benefits of Slavery”
Beginning this week, Google will roll out the ability to access Gemini right from within Google Messages on any Android device. It’s called Chat with Gemini, and like a chatbot in apps like Slack, you’ll be able to dialogue with it to draft messages, plan events, and pin ideas. You won’t have to install the Gemini app to access this feature.
Even if you don’t plan to interact with Gemini, more AI infusions are coming to an Android device near you. For those who use Android Auto behind the wheel, your car can summarize long texts and noisy group chats. The AI will also talk you through possible replies and other things you can do as you keep your eyes on the road. But speaking from experience, I hope this won’t be one of those interactions that require you to enunciate directly.
Lookout on Android, a built-in feature geared toward blind and low-vision users, will now offer auto-generated AI descriptions of photos and images that come through with messages. There’s also enhanced screen reader support for Lens inside Maps, so when you point your AR camera at a building or storefront, TalkBack will dictate what’s ahead and its entry into Google Maps.
Android watchwearers, first, let me say it’s nice to have you here. You should know that Google will allow you to access tickets, passes, and other necessary wallet staples from your wrist in the next Wear OS update. Transit directions will also be available soon, making it much easier to recall the train or bus you’re supposed to catch without taking out your phone.
Health Connect is the last portion of this mini-news maelstrom. This latest update pipes in all your third-party health data from apps like AllTrails and MyFitnessPal and aggregates them into the Today tab in the Fitbit app. I’m curious about what’s going on with this particular data-sharing suite since Google rolled it out last year. I’ll be testing this more closely as it rolls out.
Nvidia CEO Jensen Huang attends a media roundtable meeting in Singapore on Dec. 6, 2023.
Edgar Su | Reuters
Nvidia reported fourth fiscal quarter earnings that beat Wall Street’s forecast for earnings and sales, and said that revenue during the current quarter would be better than expected, even against elevated expectations for massive growth.
Nvidia shares rose about 6% in extended trading.
Here’s what the company reported compared with what Wall Street was expecting for the quarter ending in January, based on a survey of analysts by LSEG, formerly known as Refinitiv:
Earnings: $5.15 per share, adjusted, versus $4.64 per share expected.
Revenue: $22.10 billion, versus $20.62 billion expected.
Nvidia said it expected $24.0 billion in sales in the current quarter. Analysts polled by LSEG were looking for $5.00 per share on $22.17 billion in sales.Â
Nvidia reported $12.29 billion in net income during the quarter, or $4.93 per share, up 769% versus last yearâs $1.41 billion or 57 cents per share.Â
Nvidia has been the primary beneficiary of the recent technology industry obsession with large artificial intelligence models, which are developed on the company’s pricey graphics processors for servers.
Nvidia’s total revenue rose 265% from a year ago, based on strong sales for AI chips for servers, particularly the company’s “Hopper” chips like the H100, it said.
“Strong demand was driven by enterprise software and consumer internet applications, and multiple industry verticals including automotive, financial services, and healthcare,” the company said in commentary provided to investors.
Those sales are reported in the company’s Data Center business, which now comprises the majority of Nvidia’s revenue. Data center sales were up 409% to $18.40 billion. Over half of the company’s data center sales went to large cloud providers.
Nvidia said its data center revenue was hurt by recent U.S. restrictions on exporting advanced AI semiconductors to China.
The company’s gaming business, which includes graphics cards for laptops and PCs, was merely up 56% year-over-year to $2.87 billion. Graphics cards for gaming used to be Nvidia’s primary business before its AI chips started taking off, and some of Nvidia’s graphics cards can be used for AI.
Nvidia’s smaller businesses did not show the same meteoric growth. Its automotive business declined 4% to $281 million in sales, and its OEM and other business, which includes crypto chips, rose 7% to $90 million. Nvidia’s business making graphics hardware for professional applications rose 105% to $463 million.
Capital One’s recently announced $35.3 billion acquisition of Discover Financial isn’t just about getting bigger â gaining “scale” in Wall Street-speak â it’s a bid to protect itself against a rising tide of fintech and regulatory threats.
It’s a chess move by one of the savviest long-term thinkers in American finance, Capital One CEO Richard Fairbank. As a co-founder of a top 10 U.S. bank by assets, his tenure is a rarity in a banking world dominated by institutions like JPMorgan Chase that trace their origins to shortly after the signing of the Declaration of Independence.
Fairbank, who became a billionaire by building Capital One into a credit card giant since its 1994 IPO, is betting that buying rival card company Discover will better position the company for global payments’ murky future. The industry is a dynamic web where players of all stripes â from traditional banks to fintech players and tech giants â are all seeking to stake out a corner in a market worth trillions of dollars by eating into incumbents’ share amid the rapid growth of e-commerce and digital payments.
“This deal gives the company a stronger hand to battle other banks, fintechs and big tech companies,” said Sanjay Sakhrani, the veteran KBW retail finance analyst. “The more that they can separate themselves from the pack, the more they can future-proof themselves.”
The deal, if approved, enables Capital One to leapfrog JPMorgan as the biggest credit card company by loans, and solidifies its position as the third largest by purchase volume. It also adds heft to Capital One’s banking operations with $109 billion in total deposits from Discover’s digital bank and helps the combined entity shave $1.5 billion in expenses by 2027.
But it’s Discover’s payments network â the “rails” that shuffle digital dollars between consumers and merchants, collecting tolls along the way â that Fairbank repeatedly praised Tuesday when analysts queried him on the strategic merits of the deal. There are only four major card networks: giants Visa and Mastercard, then American Express and finally the smallest of the group, Discover.
Capital One and Discover credit cards arranged in Germantown, New York, US, on Tuesday, Feb. 20, 2024.Â
Angus Mordant | Bloomberg | Getty Images
“That network is a very, very rare asset,” Fairbank said. “We have always had a belief that the Holy Grail is to be able to be an issuer with one’s own network so that one can deal directly with merchants.”
From the time of Capital One’s founding in the late 1980s, Fairbank said, he envisioned creating a global digital payments tech company by owning the payment rails and dealing directly with merchants. In the decades since, Capital One has been ahead of stodgier banks, gaining a reputation in tech circles for being forward-thinking and for its early adoption of cloud computing and agile software development.
But its growth has relied on Visa and Mastercard, which accounted for the vast majority of payment volumes last year, processing nearly $10 trillion in the U.S. between them.
Capital One intends to boost the Discover network, which carried $550 billion in transactions last year, by quickly switching all of its debit volume there, as well as a growing share of its credit card flows over time.
By 2027, the bank expects to add at least $175 billion in payments and 25 million of its cardholders onto the Discover network.
The true potential of the Discover deal, though, is what it allows Capital One to do in the future if it owns the toll road, according to analysts.
By creating an end-to-end ecosystem that is more of a closed loop between shoppers and merchants, it could fend off competition from rapidly mutating fintech players like Block and PayPal, as well as buy now, pay later firms like Affirm and Klarna, who have made inroads with both businesses and consumers.
Capital One aims to deepen relationships with merchants by showing them how to boost sales, helping them prevent fraud and providing data insights, Fairbank said Tuesday, all of which makes them harder to dislodge. It can use some of the network fees to create new loyalty plans, like debit rewards programs, or underwrite merchant incentives or experiences, according to analysts.
“Owning a network allows us to deal more directly with merchants rather than a network intermediary,” Fairbank told analysts. “We create more value for merchants, small businesses and consumers and capture the additional economics from vertical integration.”
It’s a capability that technology or fintech companies probably covet. The Discover network alone would be worth up to $6 billion if sold to Alphabet,Apple or Fiserv, Sakhrani wrote Tuesday in a research note.
The Capital One-Discover combination could fortify the company against another potential threat â from Washington.
Proposed legislation from Sen. Dick Durbin, D-Ill., aims to cap the fees charged by Visa and Mastercard, potentially blowing up the economics of credit card rewards programs. If that proposal becomes law, the competitive position of Discover’s network, which is exempt from the limitations, suddenly improves, according to Brian Graham, co-founder of advisory firm Klaros Group. That mirrors what an earlier law known as the Durbin amendment did for debit cards.
Chairman Dick Durbin (D-IL) speaks during a US Senate Judiciary Committee hearing regarding Supreme Court ethics reform, on Capitol Hill in Washington, DC, on May 2, 2023.
Mandel Ngan | AFP | Getty Images
“There are a bunch of things aimed, in one way or another, at the card networks and that ecosystem,” Graham said. “Those pressures might be one of the things that creates an opportunity for Capital One in the future if they have control over this network.”
The biggest question for Capital One, its customers and investors is whether the merger will ultimately be approved by regulators. While Fairbank said he expects the deal to be closed in late 2024 or early 2025, industry experts said it was impossible to know whether it will be blocked by regulators, like a string of high-profile takeovers among banks, airlines and tech companies.
On Tuesday, Democratic Sen. Elizabeth Warren of Massachusetts urged regulators to swiftly block the deal, calling it “dangerous.” Sen. Sherrod Brown, D-Ohio, chairman of the Senate Banking Committee, said he would be watching the deal to “ensure that this merger doesn’t enrich shareholders and executives at the expense of consumers and small businesses.”
The Discover deal’s survival may hinge on whether it’s seen as boosting an also-ran payments network, or allowing an already-dominant card lender to level up in size â another reason Fairbank may have played up the importance of the network.
“Which thing you are more concerned about will define whether you think this is a good deal or a bad deal from a public policy point of view,” Graham said.
Traders work on the floor of the New York Stock Exchange during morning trading on January 31, 2024 in New York City.
Michael M. Santiago | Getty Images
The so-called “Magnificent 7” now wields greater financial might than almost every other major country in the world, according to new Deutsche Bank research.
The meteoric rise in the profits and market capitalizations of the Magnificent 7 U.S. tech behemoths â Apple, Amazon, Alphabet, Meta, Microsoft, Nvidia and Tesla â outstrip those of all listed companies in almost every G20 country, the bank said in a research note Tuesday. Of the non-U.S. G20 countries, only China and Japan (and the latter, only just) have greater profits when their listed companies are combined.
Deutsche Bank analysts highlighted that the Magnificent 7’s combined market cap alone would make it the second-largest country stock exchange in the world, double that of Japan in fourth. Microsoft and Apple, individually, have similar market caps to all combined listed companies in each of France, Saudi Arabia and the U.K, they added.
However, this level of concentration has led some analysts to voice concerns over related risks in the U.S. and global stock market.
Jim Reid, Deutsche Bank’s head of global economics and thematic research, cautioned in a follow-up note last week that the U.S. stock market is “rivalling 2000 and 1929 in terms of being its most concentrated in history.”
Deutsche analyzed the trajectories of all 36 companies that have been in the top five most valuable in the S&P 500 since the mid-1960s.
Reid noted that while big companies eventually tended to drop out of the top five as investment trends and profit outlooks evolved, 20 of the 36 that have populated that upper bracket are still in the top 50 today.
“Of the Mag 7 in the current top 5, Microsoft has been there for all but 4 months since 1997. Apple ever present since December 2009, Alphabet for all but two months since August 2012 and Amazon since January 2017. The newest entrant has been Nvidia which has been there since H1 last year,” he said.
Tesla had a run of 13 months in the top five most valuable companies in 2021/22 but is now down to 10th, with the share price having fallen by around 20% since the start of 2024. By contrast, Nvidia’s stock has continued to surge, adding almost 47% since the turn of the year.
“So, at the edges the Mag 7 have some volatility around the position of its members, and you can question their overall valuations, but the core of the group have been the largest and most successful companies in the US and with it the world for many years now,” Reid added.
Could the gains broaden out?
Despite a muted global economic outlook at the start of 2023, stock market returns on Wall Street were impressive, but heavily concentrated among the Magnificent Seven, which benefitted strongly from the AI hype and rate cut expectations.
In a research note last week, wealth manager Evelyn Partners highlighted that the Magnificent 7 returned an incredible 107% over 2023, far outpacing the broader MSCI USA index, which delivered a still healthy but relatively paltry 27% to investors.
Daniel Casali, chief investment strategist at Evelyn Partners, suggested that signs are emerging that opportunities in U.S. stocks could broaden out beyond the 7 megacaps this year for two reasons, the first of which is the resilience of the U.S. economy.
“Despite rising interest rates, company sales and earnings have been resilient. This can be attributed to businesses being more disciplined on managing their costs and households having higher levels of savings built up during the pandemic. In addition, the U.S. labour market is healthy with nearly three million jobs added during 2023,” Casali said.
The second factor is improving margins, which Casali said indicates that companies have adeptly raised prices and passed the impact of higher inflation onto customers.
“Although wages have risen, they haven’t kept pace with those price rises, leading to a decline in employment costs as a proportion of the price of goods and services,” Casali said.
“Factors, including China joining the World Trade Organisation and technological advances, have enabled an increased supply of labour and accessibility to overseas job markets. This has contributed to improving profit margins, supporting earnings growth. We see this trend continuing.”
When the market is so heavily weighted toward a small number of stocks and one particular theme â notably AI â there is a risk of missed investment opportunities, Casali said.
Many of the 493 other S&P 500 stocks have struggled over the past year, but he suggested that some could start to participate in the rally if the two aforementioned factors continue to fuel the economy.
“Given AI-led stocks’ stellar performance in 2023 and the beginning of this year, investors may feel inclined to continue to back them,” he said.
“But, if the rally starts to widen, investors could miss out on other opportunities beyond the Magnificent Seven stocks.”
As consumers watch their wallets, companies have felt pressure from investors to do the same. Executives have sought to show shareholders that they’re adjusting to consumer demand as it returns to typical patterns or even softens, as well as aggressively countering higher expenses.
Airlines, automakers, media companies and package giant UPS are all digesting new labor contracts that gave raises to tens of thousands of workers and drove costs higher.
Companies in years past could get away with passing on higher costs to customers who were willing to splurge on everything from new appliances to beach vacations. But businesses’ pricing power has waned, so executives are looking for other ways to manage the budget â or squeeze out more profits, said Gregory Daco, chief economist for EY.
“You are in an environment where cost fatigue is very much part of the equation for consumers and business leaders,” Daco said. “The cost of most everything is much higher than it was before the pandemic, whether it’s goods, inputs, equipment, labor, even interest rates.”
There are some exceptions to the recent cost-cutting wave: Walmart, for example, said last month that it would build or convert more than 150 stores over the next five years, along with a more than $9 billion investment to modernize many of its current stores.
And some companies, such as banks, already made deep cuts. Five of the largest banks, including Wells Fargo and Goldman Sachs, together eliminated more than 20,000 jobs in 2023. Now, they’re awaiting interest rate cuts by the Federal Reserve that would free up cash for pent-up mergers and acquisitions.
But cost reductions unveiled in even just the first few weeks of the year amount to tens of thousands of jobs and billions of dollars. In January, U.S. companies announced 82,307 job cuts, more than double the number in December, while still down 20% from a year ago, according to Challenger, Gray and Christmas.
And the tightening of months prior is already showing up in financial reports.
So far this earnings season, results have indicated that companies have focused on driving profits higher without the tailwind of big price increases and sales growth.
As of mid-February, more than three-quarters of the S&P 500 had reported fourth-quarter results, with far more earnings beats than revenue beats. The quarter’s earnings, measured by a composite of S&P 500 companies, are on pace to rise nearly 10%. Revenues, however, are up a more modest 3.4%.
And the layoffs haven’t been contained to tech. UPS said it was axing 12,000 jobs, saving the company $1 billion, CEO Carol Tome said late last month, citing softer demand. Many of the largest retail, media and entertainment companies have also announced workforce reductions, in addition to other cuts.
Warner Bros. Discovery has slashed content spending and headcount as part of $4 billion in total cost savings from the merger of Discovery and WarnerMedia. Disney initially promised $5.5 billion in cost reductions in 2023, fueled by 7,000 layoffs. The company has since increased its savings promise to $7.5 billion, and executives suggested in its Feb. 7 quarterly earnings report that it may exceed that target.
JetBlue Airways, which hasn’t posted an annual profit since before the pandemic, is deferring about $2.5 billion in capital expenditures on new Airbus planes to the end of the decade, culling unprofitable routes and redeploying aircraft in addition to the worker buyouts.
Some cuts are even making their way to the front of the cabin. United Airlines, which also posted a profit in 2023, at the start of this year said it would serve first-class meals only on flights more than 900 miles, up from 800 miles previously. “On flights that are 301 to 900 miles, United First customers can expect an offering from the premium snack basket,” according to an internal post.
Several of the country’s largest automakers, such as General Motors and Ford Motor, have lowered spending by billions of dollars through reduced or delayed investments on all-electric vehicles. The U.S.-based companies as well as others, such as Netherlands-based Stellantis, have recently reduced headcount and payroll through voluntary buyouts or layoffs.
Even Chipotle, which reported more foot traffic and sales at its restaurants in the most recently reported quarter, is chasing higher productivity by testing an avocado-scooping robot called the Autocado that shortens the time it takes to make guacamole. It’s also testing another robot that can put together burrito bowls and salads. The robots, if expanded to other stores, could help cut costs by minimizing food waste or reducing the number of workers needed for those tasks.
Industry experts have chalked up some recent cuts to companies catching their breath â and taking a hard look at how they operate â after an unusual four-year stretch caused by the pandemic and its fallout.
EY’s Daco said the past few years have been marked by a mismatch in supply and demand when it comes to goods, services and even workers.
Customers went on shopping sprees, fueled by government stimulus and less experience-related spending. Airlines saw demand disappear and then skyrocket. Companies furloughed workers in the early pandemic and then struggled to fill jobs.
He said he expects companies this year to “search for an equilibrium.”
“You’re seeing a rebalancing happening in the labor markets, in the capital markets,” he said. “And that rebalancing is still going to play out and gradually lead to a more sustainable environment of lower inflation and lower interest rates, and perhaps a little bit slower growth.”
The auto industry, for example, faced a supply issue during much of the Covid pandemic but is now facing a potential demand problem. Inventories of new vehicles are rising â surpassing 2.5 million units and 71 days’ supply toward the end of 2023, up 57% year over year, according to Cox Automotive â forcing automakers to extend more discounts in an effort to move cars and trucks off dealer lots.
Automakers have also been contending with slower-than-expected adoption of EVs.
David Silverman, a retail analyst at Fitch Ratings, said companies are “feeling a bit heavy as sales growth moderates and maybe even declines.”
Cost cuts at UPS, Hasbro and Levi all followed sales declines in the most recent fiscal quarter. Macy’s, which reports earnings later this month, has said it expects same-store sales to drop, and there’s early evidence that may come to bear: Consumers pulled back on spending in January, with retail sales falling 0.8%, more than economists expected, according to the latest federal data.
Most major retailers, including Walmart, Target and Home Depot, will report earnings in the coming weeks.
Credit ratings agency Fitch said it doesn’t expect the U.S. economy to tip into recession, but it does anticipate a continued pullback in discretionary spending.
“Part of companies’ decision to lower their expense structure is in line with their views that 2024 may not be a fantastic year from a top-line-growth standpoint,” Silverman said.
Plus, he added, companies have had to find cash to fund investments in newer technology such as infrastructure that supports e-commerce, a resilient supply chain or investments in artificial intelligence.
Companies may have another reason to cut costs now, too. As they see other companies shrinking the size of their workforces or budgets, there’s safety in numbers.
Or as Silverman noted, “layoffs beget layoffs.”
“As companies have started to announce them it becomes normalized,” he said. “There’s less of a stigma.”
Even with rolling layoffs, the labor market remains strong, which may help explain why Wall Street has by and large rewarded those companies that have found areas to save and returned profits to shareholders.
Shares of Meta, for example, almost tripled in price in 2023 in that “year of efficiency,” making the stock the second-best gainer in the S&P 500, behind only Nvidia. After laying off more than 20,000 workers in 2023, Meta on Feb. 2 announced its first-ever dividend and said it expanded its share buyback authorization by $50 billion.
UPS, fresh from job cuts, said it would raise its quarterly dividend by a penny.
Overall, dividends paid by companies in the S&P 500 rose 5.05% last year, according to Howard Silverblatt, senior index analyst at S&P Dow Jones Indices, and he estimated they will likely increase nearly 5.3% this year.
â CNBC’s Michael Wayland, Alex Sherman, Robert Hum, Amelia Lucas and Jonathan Vanian contributed to this story.
Disclosure: Comcast owns NBCUniversal, the parent company of CNBC.
With the S & P 500 on Friday closing above 5,000 for the first time ever, recognizing the winners this year has not been difficult. But what about the ones that are still cheap â or less expensive â on a valuation basis? Those are not as easy to spot. We screened the 32 stocks in our portfolio late Monday and identified 10 that are undervalued based on traditional market metrics following their latest quarterly earnings reports. (The market was under heavy pressure Tuesday after a hotter-than-expected consumer price index.) To determine valuation, we reviewed two metrics â price-to-earnings (P/E) ratios and P/E-to-growth (PEG) ratios â and compared each to their historical five-year averages. P/Es and PEG ratios A stock’s P/E shows how much shareholders are paying in share price for earnings. We use forward P/Es in our analysis. A stock with a lower P/E is considered to be cheaper on a valuation basis. Sometimes, however, a low P/E could be a red flag â signaling earnings estimates are too high and need to come down, which usually leads to a drop in share price, or something is fundamentally wrong with the company, such as slowing growth. The PEG ratio, another valuation tool, starts with the price-to-earnings ratio and divides the P/E by estimated earnings growth. This metric helps investors determine whether they’re paying too much today for a company’s estimated growth in the future. A good PEG ratio is 1 or lower. There is a major consideration when analyzing five-year valuation average comparisons: interest rates. As inflation has cooled, there has been a debate recently over when central bankers should cut rates. If rates come down this year, as expected, then higher multiples could be supported. The 10 undervalued companies from our screen all have strong businesses. Some of these stocks, like the overall market, are trading at or near record-high prices. But price is what you pay and value is what you get. Stocks can have high prices based on historical trading patterns and still be considered cheap based on valuation. As a yardstick, the S & P 500 has a price-to-earnings multiple of 20.5 times the next 12 months’ earnings estimates. That’s above its five-year average of 18.9. The stocks we’re highlighting here are all trading below their five-year average. In other words, the overall market is more expensive compared to historical norms and these stocks are less expensive. All data is from FactSet as of Monday. 1. Alphabet Price-to-earnings ratio (P/E): 21.1 P/E vs. peers: 10% cheaper P/E-to-growth ratio (PEG): 1.3 Alphabet ‘s forward P/E of 21.5 times is 10% cheaper than peers and below its five-year average of 23.4. The PEG of 1.3 is below the historical average of 1.5 â meaning you’re paying less for estimated growth, too. Alphabet shares have the cheapest valuation of all our Significant Six mega-cap tech stocks, which include Amazon, Apple , Microsoft , Meta Platforms and Nvidia. Alphabet’s attractive valuation comes despite multiple avenues for growth within Google Cloud and generative artificial intelligence through Gemini, the successor to Bard. Ongoing cost discipline should also benefit margin expansion. While advertising revenue came in softer than anticipated in Alphabet’s most recent quarter , we believe the tech firm’s use of gen AI in Google search can help improve results. GOOGL 5Y mountain Alphabet 5 years The stock would need to gain about 4% to reach last month’s all-time high. We have our wait-for-a-pullback 2 rating on shares because it’s not our style to chase moves higher even if the valuation is attractive. 2. Amazon Price-to-earnings ratio (P/E): 40.9 P/E vs. peers: flat P/E-to-growth ratio (PEG): 1.3 Amazon ‘s forward P/E of 40.9 times is relatively flat compared to peers and well below its five-year average of 62.7. The PEG of 1.2 is half its historical average. The bargain here is on growth versus what was paid for Amazon’s growth in the past. That’s significant. Amazon shows promise in delivering consistent revenue and earnings growth in the years to come. Profitability in retail is incrementally growing as management focuses on speeding up delivery times supported by the regionalization of its fulfillment network. Cost efficiencies also show the strength of its operating margin growth opportunity across segments. Amazon continues to exhibit strong advertising revenue growth, and the company’s Amazon Web Services cloud unit is back and presents a major multiyear growth opportunity. AMZN 5Y mountain Amazon 5 years Shares of Amazon hit a 52-week high Monday but would still have to increase 9% to hit their July 2021 all-time closing high. For the same reasons as Alphabet, we have a 2 rating on Amazon shares. 3. Constellation Brands Price-to-earnings ratio (P/E): 18.1 P/E vs. peers: flat P/E-to-growth ratio (PEG): 1.8 Constellation Brands ‘ forward P/E of 18.1 times roughly the same as peers and below its five-year average of 20.2. The PEG of 1.8 is well below its historical norm of 2.7. So again, cheaper all around. The maker of Corona, Modelo, and Pacifico delivered a largely positive third quarter last month, with its core Beer business delivering solid results during an off-season period. The company’s struggling Wine & Spirits segment continued to disappoint. Jim Cramer has said over and over that Constellation should concentrate on Beer and offload Wine & Spirits. Management reaffirmed its consolidated comparable earnings guidance while raising its full-year outlook for operating and free cash flow. Shares of Constellation would need to add 10% to match their record closing high of nearly $273 each back in July. We think the stock can get back to those levels. And with an attractive valuation to boost, we have the stock at our buy-equivalent 1 rating. 4. Disney Price-to-earnings ratio (P/E): 22.3 P/E vs. peers: 20% cheaper P/E-to-growth ratio (PEG): 1.2 Disney stock is undervalued even with shares rallying roughly 12% after the company reported an upbeat fiscal 2024 first quarter. The company’s P/E ratio of 21.5 times is about 20% cheaper than peers and below its historical average of 29.6. The PEG of 1.2 compared to its historical 2.6 also flashes bargain, too. Nelson Peltz sees “undervalued” as a problem here. That’s why the activist investor is fighting for Disney board seats. Jim has said he wants Disney’s board to have more “skin in the game,” meaning more share ownership among its members. Peltz would bring that and past success in creating more shareholder value. Disney doesn’t want Peltz on the board, saying outside distractions are not what the company needs. CEO Bob Iger was able to show strength in parks as well as some progress in the entertainment giant’s financials. Management delivered improved profitability, cut streaming losses, and issued guidance of earnings-per-share growing at least 20% for fiscal year 2024 compared to the prior year. However, advertising trends in Disney’s linear networks have been weak as customers migrate to streaming services and a series of the company’s recent films have been duds at the box office. Disney would have to nearly double to get back to its March 2021 all-time closing high of almost $202 per share. We know the turnaround at Disney is going to take a while. But with an inexpensive valuation and an emerging path to growth ahead, we have a 1 rating on the stock. 5. Honeywell Price-to-earnings ratio (P/E): 19.4 P/E vs. peers: 10% cheaper P/E-to-growth ratio (PEG): 2.3 We like how Honeywell ‘s stock is valued post-earnings . The forward P/E of 19.4 times is 10% cheaper than peers and below its five-year average of 21.5. The PEG of 2.3 versus its average of 2.8. Shares pulled back about 3% after the company reported lower-than-expected organic sales. But what Wall Street didn’t credit was the company had better margins, cash flow and solid backlog. We bought shares on weakness on earnings day Feb. 1 because we still believe in the long-term for the industrial giant’s strong execution. While sales were disappointing. Honeywell’s historically strong Aerospace segment continued to deliver. However, the company is still dealing with softness in its Safety and Productivity Solutions as well as Building Technologies segments. HON 5Y mountain Honeywell 5 years Honeywell shares still need to gain nearly 20% to get back to its record close of just over $234 each back in August 2021. We have a 1 rating on the stock, appreciating its valuation and long-term prospects. 6. Nvidia Price-to-earnings ratio (P/E): 33.5 P/E vs. peers: 10% most expensive P/E-to-growth ratio (PEG): 0.8 After Nvidia ‘s stellar triple in 2023, shares still screen cheap even after its 40% year-to-date gain. In terms of valuation, Nvidia is attractive boasting a forward P/E of 33.5 times. That’s about 10% higher than peers but you could argue that it deserves it due to its utter domination of the market for semiconductors that can artificial intelligence. Not to mention, Nvidia’s P/E is still lower than its historical average of 39.6. Add in the PEG, at a reading of 0.8 versus the 2.2 five-year average, and that’s a dirt cheap cost for expected sky-high growth. NVDA 5Y mountain Nvidia 5 years As every day seems to bring a new high lately, we have a 2 rating on the stock in recognition that we don’t want to chase this runaway train higher. But we still believe Nvidia should be part of any long-term portfolio. We explain in a recent commentary how investors with no Nvidia position (or no positions in the rest of our Significant Six), might think about getting in. 7. Salesforce Price-to-earnings ratio (P/E): 30.3 P/E vs. peers: 10% cheaper P/E-to-growth ratio (PEG): 1.4 Salesforce ‘s forward P/E of 30.3 times â 10% cheaper than peers and below its historical average of 46 âand a PEG of 1.4 versus its five-year average of 2.5 show how undervalued the stock is. Back in November , the consumer relationship management software company reported a solid fiscal 2024 third quarter. (The most recent quarter comes at the end of February.) Management at the time boasted solid deal activity even after the tech giant hiked prices on some of its products. The company’s guidance was also upbeat as it expects to grow revenue at a solid pace, accompanied by margin gains. CRM 5Y mountain Salesforce 5 years The stock has been on a tear and would need to add only 7.6% to reach its nearly $310 all-time closing high in November 2021. Shares hit a 52-week high last week. Acknowledging the run, we have a 2 rating on the stock. 8. Starbucks Price-to-earnings ratio (P/E): 22.5 P/E vs. peers: 10% cheaper P/E-to-growth ratio (PEG): 1.3 Starbucks ‘ forward P/E ratio of 22.5 times is 10% cheaper than peers and below its 5-year average of 28.3. The PEG at 1.3 is below its historical average of 2. Both indicators reflect an undervalued stock. But similar to Disney, those low readings might also signal caution. We know from its fiscal 2024 first quarter results, out last month , that the company is facing headwinds such as a slowdown in business due to Middle East protests and sluggish economic activity in China. These are factors that could impact growth. SBUX 5Y mountain Starbucks 5 years However, even when we take this into account, the stock has fallen way too much. Starbucks would have to gain more than 30% to eclipse its July 2021 record close of $126 per share. If we consider growth may be a little slower due to the Israel-Hamas war protests and China rebounding slower than expected, we’re still seeing a good value in Starbucks shares. We have a 1 rating, accordingly. 9. Wells Fargo Price-to-earnings ratio (P/E): 9.9 P/E vs. peers: 10% cheaper P/E-to-growth ratio (PEG): 0.7 Wells Fargo ‘s forward P/E of 9.9 is 10% cheaper than peers and lower than the 11.2 five-year average. The PEG under 1 â in this case 0.7 â is low, especially when you compare it to a historical average of 1.1. Are these low numbers a sign of trouble? We don’t think so. While Wells Fargo stock came under pressure following conservative guidance, the bank’s fourth-quarter earnings report was solid. It beat on both net interest income and noninterest income. We have come to expect CEO Charlie Scharf to set measured expectations, which can be beaten. We like how management is managing and reducing expenses on a year-over-year basis, which balances the softer outlook. Wells Fargo also expects to buy back more shares in 2024 compared to last year, which adds to shareholder value. While hitting a 52-week high at the end of January, Wells Fargo stock would need to gain roughly 35% to get back to its January 2018 record close of nearly $66. But a cheap valuation coupled with an industry getting further and further away from last year’s regional lender crisis after the collapse of Silicon Valley Bank in March 2023 leads us to our 1 rating 10. Wynn Resorts EV-to-EBITDA (enterprice value/earnings before interest, taxes, and amortization): 9.1 We’re mixing it up a bit with Wynn Resorts â focusing on the company’s adjusted EBITDA because this is the financial metric of choice on Wall Street when it comes to the best-in-class hotel and casino operator. With adjusted EBITDA being the key metric, the multiple we’re focused on is enterprise value to forward EBITDA. Before Covid, Wynn generally traded in a range of about 9 times to 13 times â with two very brief periods in late 2015 and late 2018 where the multiple was closer to 8 times EV/EBITDA. However, with shares now trading at roughly 9.1 times EV/EBITDA on a forward basis, we find them highly attractive given what we just heard from management. WYNN 5Y mountain Wynn Resorts 5 years Investors received a positive update on Wynn ‘s financials when it reported beats on its top and bottom lines in its fourth quarter . Macao is coming back, while Las Vegas is strong and Boston Harbor is resilient. It seems even cheaper when considering that China isn’t fully back online yet, but the company is already operating at structurally higher profit margins compared to historical norms. We added to our Wynn position with a small buy last Thursday after its stronger-than-expected quarter because we think the stock has more room to run. (Jim Cramer’s Charitable Trust is long GOOGL, AMZN, STZ, DIS, HON, NVDA, SBUX, CRM, WFC, WYNN. See here for a full list of the stocks.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust’s portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.
A trader works on the floor of the New York Stock Exchange
Michael Nagle | Bloomberg | Getty Images
With the S&P 500 on Friday closing above 5,000 for the first time ever, recognizing the winners this year has not been difficult. But what about the ones that are still cheap â or less expensive â on a valuation basis? Those are not as easy to spot.
We screened the 32 stocks in our portfolio late Monday and identified 10 that are undervalued based on traditional market metrics following their latest quarterly earnings reports. (The market was under heavy pressure Tuesday after a hotter-than-expected consumer price index.)
Daryn Carr is no stranger to side hustles. After his mom died from Covid in 2020, he used funds from her pension to pay off some bills and buy a car. With the remaining money, he invested in crypto and started an ATM business.
One day in 2022, while scrolling through Instagram, he came upon another opportunity. Carr found a guy named Anthony Agyeman,who was promoting a type of arbitrage on Airbnb that involved taking listings from hotel booking and short-term rental sites and relisting them on Airbnb at a higher price, retaining the profit.
Agyeman claimed in marketing materials that his business, Hands-Free Automation, had “5-year exclusivity contracts” with thousands of property owners that gave it permission to relist their properties at a higher price.
Getting involved with Hands-Free Automation, or HFA, required a payment of between $20,000 and $30,000 to effectively own a piece of Airbnb listings. Agyeman described it as a “minimal to no risk” path to extra income with a guaranteed return in three to six months of investment, “then pure profit after.”
HFA has no affiliation with Airbnb but found a way to make money on the marketplace using a practice that Airbnb explicitly prohibits. Agyeman was following similar tactics that he’d used on Amazon and Shopify, where he promoted the opportunity for investors to passively own virtual storefronts.
The tech companies that own these marketplaces all say they use a combination of artificial intelligence and automation along with manual reviews to monitor vendor and customer activity for fraud and other misbehavior, but they’ve been ill-equipped to deal with the volume of complaints stemming from various sorts of scams.
The Federal Trade Commission and the Department of Justice have cracked down on companies similar to HFA, accusing them ofadvertising their products with false promises of profit and successandallegedly selling “automated” software that didn’t work. HFA and Agyeman haven’t been charged by the Justice Department, FTC or any law enforcement agency.
Airbnb told CNBC it was unaware of any contact from regulators regarding HFA.
For a clearer picture of HFA’s inner workings, CNBC spoke with investors in a lawsuit filed against the company in February 2023, as well as six former HFA employees, an Airbnb customer who unwittingly stayed at an HFA-listed property, and a property owner who said his listings were uploaded to Airbnb by HFA without permission. CNBC has granted anonymity to those who requested it because they weren’t authorized to speak publicly on HFA’s operations, or feared retribution from the company.
Brian Chesky, co-founder and CEO of Airbnb, Inc., speaks during an interview with CNBC on the floor of the New York Stock Exchange in New York City, May 10, 2023.
Brendan McDermid | Reuters
Carr, who lives in New York, wired HFA $1,000 through his crypto debit card at the urging of a salesperson and borrowed an additional $18,490 to pay for HFA’s entry-level package. In total, Carr paid HFA $19,497, according to the lawsuit, which Carr filed along with 11 other investors. The plaintiffs alleged that HFA falsely claimed it had relationships with the properties, and that HFA’s services violated Airbnb’s terms of service. The case is still proceeding.
Carr told CNBC that his investment with HFA disappeared, leaving him in debt and working a customer service job to make ends meet. He claims he got scammed and suspects that much of his money went toward subsidizing Agyeman’s lifestyle.
“I couldn’t believe that I lost $20,000 into thin air,” Carr said.
Thomas Hunker, an attorney for Agyeman and HFA, denied that customer money had been used for anything except the business.
“We have always honored our fiduciary obligations with respect to allocation of company money in the best interest of the company,” Hunker said in a written response to CNBC.
HFA admitted to customers that it was “continuously encountering problems with” Airbnb “due to the constant changes they have made to their terms and services,” according to the lawsuit.
Plaintiffs in the suit against Agyeman and other defendants are asking for at least $624,000 in damages from their lost investments. Meanwhile, the defendants continue to advertise and sell products to prospective investors under a new company called Wealthway. They’re deploying a team that aims to generate more than $3.5 million in monthly sales, Wessel Botes, a former sales employee who left the company in November, told CNBC.
Hunker said in an email to CNBC that HFA identifies properties to list from third-party websites used by hotels and other property owners to “increase bookings.” That gives HFA “indirect permission” through those third-party sites to relist rooms on Airbnb, he said, adding that the base price of the booking goes back to the property owner.
“Using a 3rd party to book a hotel or 3rd party accommodation and listing it on Airbnb at an inflated rate is not allowed,” the policy says.
Airbnb told CNBC that business practices such as Agyeman’s aren’t permitted. The company said it continues to improve systems that identify and remove fake or misleading listings, adding that it had blocked more than 216,000 suspicious listings as of September.
Hunker said HFA doesn’t have investors, but rather has clients who pay a “flat fee” for an arbitrage service. Yet, HFA says on its LinkedIn page that it helps “Airbnb investors add 300+ properties to their account without having to purchase the properties.”
Before connecting CNBC with his attorney, Agyeman said in an interview that he wasn’t involved in the day-to-day operations at HFA and he denied any financial improprieties.
Airbnb told CNBC it had no business relationship with Agyeman and had taken action to curtail his operations. The company said multiple accounts linked to Agyeman and HFA had been removed.
The opportunity for property owners to make money is fundamental to Airbnb’s business model. The company says that, since its founding in 2007, hosts have made more than $180 billion. En route to upending the hotel industry, Airbnb’s market cap has swelled to almost $95 billion, making it bigger than any hotel chain.
Airbnb acknowledged in its annual report that “perpetrators of fraud” use “complex and constantly evolving” tactics on the site and that “fraudsters have created fake guest accounts, fake host accounts, or both, to perpetrate financial fraud.”
Agyeman, who started HFA with co-founder Megan Shears, claims to have created proprietary software that would fully automate the arbitrage process by trawling the internet for properties to relist at a markup. HFA’s employees would take care of booking properties and handle guest inquiries and complaints.
Agyeman, 27, lives in Texas, as does Shears, 26, according to public records. Their social media posts show luxurious vacation spots next to screenshots of Airbnb bookings purportedly worth thousands of dollars. Several investors said in court filings that they first learned about Agyeman and Shears through Instagram.
“It’s proven and it works and you get higher returns than the stock market,” one HFA promotional video said.
Investors in the lawsuit say otherwise. And some customers who used the service to book travel say they lost money and were left scrambling for a place to stay.
In February 2022, a customer named Kathy booked a beachside Airbnb on Florida’s Sanibel Island for a five-night spring break vacation with her family. Kathy, who spoke on condition that CNBC not use her last name, paid $4,600 upfront for what she thought was a “fantastic” poolside one-bedroom apartment. CNBC identified Kathy as an HFA customer because her name and phone number were posted on HFA’s Instagram account.
Days went by without word from her host. Kathy, who lives in Texas, repeatedly reached out to Airbnb, but was told she’d have to engage directly with the host to cancel her booking.
Kathy looked up the property’s address on Google Maps. Rather than a tropical apartment building, she saw what appeared to be a vacant lot. “Please refund my money,” she recalled telling the host.
Desperate to make sure she had a place to stay, Kathy booked a room at a resort in Fort Myers, more than 40 miles from Sanibel Island. Ultimately, after days of back-and-forth messages, Airbnb refunded about half her money.
It ended up being “a super expensive vacation,” Kathy said. “I will never use it again,” she said of Airbnb.
For Agyeman and Shears, Airbnb was just one of their stomping grounds. They had an Amazon and Shopify automation business, a trucking business, and a line of vegan gummies. Agyeman also helped run a YouTube channel focused in part on swapping tips for running a successful business.
The duo broke into the arbitrage business in 2020. According to the lawsuit, Agyeman and Shears claimed in marketing material that they had more than 200,000 properties and had “proprietary relationships with Airbnb and Vrbo,” Expedia’s vacation rental site.
Agyeman relied on freelancers who would take data from other travel booking sites to use on their Airbnb and Vrbo listings, according to former employees and internal documents. An internal training video viewed by CNBC instructed copywriters on how to recycle the original listings’ details for Airbnb or Vrbo.
“PLEASE ANYWHERE IN THE LISTING DO NOT MENTION THAT THIS IS A HOTEL OR THE HOTEL NAMES OF THE HOTEL OR RESORTS,” a training document said.
HFA said its software algorithmically adjusted the price of a property in response to changes on the original listing. Agyeman said on social media that his employees were “the only ones tapped into Airbnb & Vrbo Arbitrage Automation.”
One spreadsheet listed 68 different clients as Airbnb investors. Going at least as far back as July 2022, HFA attracted 120-plus investors who collectively paid close to $3 million for “automated” Airbnb, Shopify, or Amazon businesses, according to internal payment tracking and financial records reviewed by CNBC.
Carr, who was listed as a property host, said that when it came to his experience with HFA, there was chaos on both sides of the marketplace. On one occasion, he said, he was contacted by the owner of a hotel who found one of its rooms on Airbnb.Another time, a woman messaged him 30 to 40 times when she couldn’t find her booking.
“People are going to the hotels saying I got an Airbnb, and they’re like, ‘What are you talking about?’” Carr said.
Carr and other HFA investors told CNBC their frustrations were dismissed or met with legal threats. But in a letter to investors cited in the lawsuit, HFA conceded that its Airbnb business had been disappointing.
“Due to Airbnb constant changes we believe this program will take much longer than anticipated to help you our client reach your goals,” HFA wrote.
Still, HFAdeclined to refund investors’ funds, instead offering them an Amazon or Shopify storefront, according to the letter and the lawsuit. Hunker said this was contemplated by the parties’ agreements.
Getting properties listed on Airbnb involved some finagling, because the company requires hosts to prove ownership. To get around Airbnb’s rules, HFA instructed its investors to list their own homes, a former employee and two investors told CNBC. Hunker denies that HFA gave those instructions. Once validated as a property owner, investors could then add more listings that HFA would pull from other websites.
Negative reviews flowed in from unhappy would-be vacationers, outraged investors and a business owner who’d discovered his property had been listed without consent.
An HFA investor told CNBC that one listing received a comment from a guest who said he paid $800 for a motel room that cost less than half that amount and described it as a “total scam.”
“Host does not own the property,” the reviewer said, according to a screenshot of the message seen by CNBC. “It is a standard motel room, no frills.”
On a hot September day in Las Vegas in 2022, another guest showed up at an MGM hotel only to discover there was no reservation through Airbnb. Neither the guest nor Airbnb could get in touch with the listed host for hours. Carr, the HFA investor host on record for the property, provided CNBC with screenshots of the messages.
“I had my family double parked on the Vegas strip for three hours wasting gas while I was running back and forth between the three MGMs in 103 degree weather being told each time after waiting in line that there was no reservation in my name,” the guest wrote.
Eventually MGM found the room had been booked through Expedia, which is where HFA turned after receiving the reservation request on Airbnb.
An Expedia spokesperson declined to comment.
Collin Ballard was shocked in May 2022, when he saw photos from his Dallas hostel advertised on Airbnb. Most alarming was the price: $1,760 a night vs. his starting nightly rate of $40.
Collin Ballard found a room from his Dallas hostel listed on Airbnb without his permission.
Collin Ballard
Ballard wrote to the host, telling him he was the owner and asking him to remove the listing.
“I just figured it was someone scamming,” Ballard said in an interview, adding that he knew nothing about Airbnb arbitrage.
Ballard said nobody ever responded to his message, but the listing was eventually taken down.
Airbnb ultimately removed most if not all of HFA’s listings over the course of several months in 2022, according to the lawsuit, though employees and investors told CNBC they weren’t sure why.
Several investors told CNBC that they encountered verification problems because it was impossible to prove they owned their listings. HFA responded by forging bills or other documents with the stolen listings’ address, according to investors, the lawsuit,an HFA training video, and a former employee.
If the allegations are true, HFA was sidestepping a key safety feature. False information can make it difficult for Airbnb to respond in an emergency or a situation that calls for the involvement of its safety team.
Airbnb told CNBC that it was rolling out a more robust verification process in the U.S. and elsewhere beginning as early as 2024.
Hunker denied allegations that HFA forges documents, and said Airbnb doesn’t require the lister to be the property owner.
By the end of last year, HFA’s investors realized that their promised gains were not materializing. Dozens unsuccessfully pressed for refunds of their deposits, according to a former employee, an internal HFA document, and the investor lawsuit.
A month after HFA’s then-counsel wrote to two dozen investors in January 2023 declining to provide refunds, investors filed their lawsuit, with 22 plaintiffs saying they received fewer than five bookings each, including 16 who said they had no bookings at all.
Hunker said HFA could present records showing its clients profited from the company’s services on the condition that CNBC sign a nondisclosure agreement. CNBC declined.
Agyeman continues promoting his businesses on social media. In his Instagram bio, he includes a new private equity venture called OKU Capital. Agyeman is its only member, according to Florida state filings and the firm’s LinkedIn profile.
Agyeman’s Wealthway advertises “fully managed,” “automated” vacation rental businesses with “minimal to no risk.” It’s similar to HFA, down to the branding on its website.
On its website, Wealthway has a video appearing to show a meeting between Agyeman and an Airbnb executive named David Levine, whose LinkedIn profile says he’s Airbnb’s head of API and enterprise partnerships for North America.
“What you guys have been doing at Wealthway is incredible and you guys have been following our partner guidelines,” Levine says in the recording.
In November, Botes, the former HFA salesman, became suspicious of the clip and sent it to Levine in a LinkedIn message.
“That video appears to have been taken out of context and altered,” Levine replied, according to screenshots of the messages viewed by CNBC. “Neither I, nor Airbnb, have any affiliation with Wealth Ways Vacation Rentals.”
Airbnb said it believes the clip is inauthentic. Levine didn’t respond to CNBC’s LinkedIn message. Hunker didn’t respond to a question about the video’s authenticity.
A display for image sharing and social media service Pinterest is seen at the Collision conference in Toronto, Ontario, Canada June 23, 2022.
Chris Helgren | Reuters
Pinterest shares plummeted in extended trading on Thursday after the company issued a weaker-than-expected forecast and missed on revenue.
Revenue: $981 million vs. $991 million expected, according to LSEG, formerly known as Refinitiv.
Earnings: 53 cents per share, adjusted, vs. 51 cents per share expected, according to LSEG.
Revenue rose 12% year-over-year from $877.2 million a year earlier, while net income was $201 million, or 29 cents a share, up from the $17.49 million, or 3 cents a share, it brought in the previous year.
Monthly active users in the fourth quarter rose 11% to 498 million, topping analyst estimates of 487 million. The company said its global average revenue per user was $2, lower than analyst estimates of $2.05.
Pinterest said first-quarter revenue will be between $690 million and $705 million, which equates to year-over-year growth of 15% to 17%. The middle of that range, $697.5 million, is below the average analyst estimate of $703 million.
The stock initially sank as much as 28% to an after-hours low of $29.40. It then pared some of its losses, climbing back to $35.19, representing a 14% decline.
The company’s report comes as the broader digital advertising market is showing recovery, with Meta, Alphabet and Amazon all picking up steam and growing their ad business by double digits in the fourth quarter. The data suggests that businesses are boosting spending on online promotions after cutting back in 2022 and part of 2023 over concerns about the Ukraine-Russian war and high interest rates.
But not all online ad companies are seeing the benefits. Snap shares cratered 35% on Wednesday after the company reported fourth-quarter sales growth of 5%, trailing expectations, and the company also issued weak guidance.
Prior to Thursday’s report, Pinterest shares were up 9.5% this year after surging 53% in 2023.
Costs dropped about 10% from a year ago to $785 million, largely due to a decline in sales and marketing expenses. A year ago Pinterest slashed about 5% of its workforce, part of an industrywide downsizing.
Here are the biggest calls on Wall Street on Wednesday: Redburn Atlantic Equities reiterates Amazon as buy Redburn said Amazon Web Services’ pricing power will drive share acceleration for Amazon. “The combination of fading optimisation headwinds, increased deployment of new workloads and the February price hike bodes well for a meaningful growth reacceleration of AWS above market expectations. Bank of America reiterates Alphabet as buy Bank of America said AI is a “top stock driver” for Alphabet “Overall, we do not see a major traffic impact for Google and continue to expect progress with AI to be top stock driver.” Leerink downgrades Amgen to market perform from outperform Leerink downgraded the biotech company due to rising obesity competition and the firm says more info is needed for Amgen’s experimental weight-loss drug. “We await data with longer-term administration to better understand drug efficacy and tolerability.” KeyBanc initiates Crocs and Deckers as overweight Key said it’s bullish on footwear companies like Crocs and Deckers. “Another Year of Macro Uncertainty Is Upon Us, but Footwear Should Remain Strong and Steady.” Gordon Haskett upgrades Target to buy from neutral Gordon Haskett said in its upgrade of the stock that “comp prospects will begin to brighten.” “Finally, in order to capitalize on our expectation for an uptick in discretionary sales we are upgrading Target to Buy.” Redburn Atlantic Equities upgrades Toast to buy from neutral Redburn said the restaurant technology company is underappreciated. ” Toast’s ability to maintain a stable gross payment take rate while onboarding larger merchants is clear evidence of pricing power on SMB [small midsize business] merchants.” Jefferies initiates Sprout Social as buy Jefferies said the social media software provider is a market leader. “We initiate on social media management software company SPT with a Buy.” Citi downgrades Steven Madden to neutral from buy Citi said in its downgrade of Steven Madden that it sees margin headwinds for the shoe company. “Margin Headwinds Limit EPS Upside in F24E; D/G to Neutral.” JPMorgan downgrades New York Community Bancorp to neutral from overweight JPMorgan said in its downgrade of the regional bank that executive departures and a disappointing earnings report earlier this week have the stock “outside of our comfort zone.” “It has been a very challenging week for NYCB shares since NYCB reported 4Q23 earnings which included (1) the company reporting a wide EPS miss on 4Q23 results (on significant provision build) and (2) a disappointing 2024 outlook tied to the bank ramping up liquidity, reserves, and capital as part of becoming a Category 4 bank ($100B+ in assets).” Jefferies upgrades Quest Diagnostics to buy from hold Jefferies said in its upgrade of Quest that the medical diagnostic’s stock is “compelling.” “U/G to Buy: Guidance Is Attainable, M & A To Drive Upside, Valuation’s Compelling.” Morgan Stanley names Huntington Bancshares a top pick Morgan Stanley said it likes the regional bank’s low exposure to commercial real estate. “Making HBAN , with its low CRE exposure and high reserve ratio our Top Pick.” Morgan Stanley reiterates Nvidia as overweight Morgan Stanley raised its price target on Nvidia to $750 per share from $603. “We continue to see a very strong near term picture, and think that various second derivative anxieties are missing the bigger picture; we raise #s yet again.” Morgan Stanley downgrades Aptiv to underweight from equal weight Morgan Stanley said it sees slowing growth for the automotic tech company. “A slowdown in demand for EVs and legacy OEMs’ willingness to make them challenges APTV’s growth-over-market (GOM) assumption which underpins earnings and valuation.” Jefferies upgrades Semrush to buy from hold Jefferies said the search engine optimization company has “pricing power.” “We assume coverage of Semrush — an SEO, competitor intelligence, and digital marketing platform— upgrading the stock to Buy from Hold.” JPMorgan upgrades Crown Holdings to overweight from neutral JPMorgan said shares of the packaging company have an attractive risk/reward. “We think that Crown Holdings has reached an equity value that leads to a favorable risk/reward balance.” Piper Sandler initiates Civitas Resources as buy Piper said shares of the energy producer are underappreciated. “We initiate coverage of Civitas Resources (CIVI) with an Overweight rating and $92 PT.” DA Davidson upgrade Symbotic to buy from neutral DA said shares of the robotic automation company are attractive. “We find SYM’s long term fundamentals attractive and its technology unrivaled and highly differentiated.” Goldman Sachs downgrades VF Corp to neutral from buy Goldman downgraded the owner of brands of like Vans and North Face and says it doesn’t see any near term positive catalysts for VF Corp. “Longer-dated path to turnaround as profit pressures persist; downgrade to Neutral.” Bank of America downgrades New York Community Bancorp to neutral from buy Bank of America said New York Community Bancorp’s outlook is too “muddled” after the recent selloff. “We believe the persistent sell-off in the stock over the last two days on perceived risks tied to the commercial real estate (CRE) book and the heightened degree of regulatory scrutiny is likely to weigh on the EPS outlook and on investor sentiment to add exposure to the stock.” DA Davidson reiterates Apple as neutral DA raised its price target on the stock to $200 per share from $166 and says it’s bullish on Apple’s Vision Pro. The firm said it was maintaining its neutral rating overall. “We are more positive on AAPL after experiencing a Vision Pro demo first hand.” Oppenheimer upgrades Enphase to outperform from perform Oppenheimer upgraded the energy company after its earnings report on Tuesday and says estimates have bottomed. “With ENPH guiding well below consensus and shares trading substantially higher, we believe the debate on shares will now focus on lingering channel inventory overhang, underlying demand levels, and the competitive landscape.” Jefferies initiates ZoomInfo as buy Jefferies initiates the software data company with a buy and says it sees new customer growth. “We initiate on sales and marketing intelligence company ZI with a Buy.’
Snap Inc. co-founder and CEO Evan Spiegel speaks during the Viva Technology conference dedicated to innovation and startups, at the Porte de Versailles exhibition center in Paris, June 17, 2022.
Benoit Tessier | Reuters
Snap on Tuesday reported revenue that trailed analysts’ estimates and issued a forecast that came in a bit below Wall Street expectations. The stock plunged 30% in extended trading.
Here’s how the company did:
Earnings per share: 8 cents adjusted vs. 6 cents expected by analysts, according to LSEG, formerly known as Refinitiv
Revenue: $1.36 billion vs. $1.38 billion expected, according to LSEG
Global daily active users: 414 million vs. 412 million expected, according to StreetAccount
Average revenue per user: $3.29 vs. $3.33 expected, according to StreetAccount
Snap has struggled to rebound from the downturn in the digital ad market and has now reported six straight quarters of single-digit growth or sales declines. For the fourth quarter, revenue rose about 5% year over year to $1.36 billion from $1.3 billion a year earlier.
The company attributed some of the weakness to the war in the Middle East, which erupted in October, beginning with Hamas’ attack on Israel.
“While we are encouraged by the progress we are making with our ad platform and the improved results we are delivering for many of our advertising partners, we estimate that the onset of the conflict in the Middle East was a headwind to year-over-year growth of approximately 2 percentage points in Q4,” Snap said in a letter to investors.
Growth is expected to accelerate in the first quarter, but not quite as fast as analysts were expecting. Snap forecast sales for the quarter of $1.095 billion to $1.135 billion, representing about 11% growth at the midpoint of the range, which was $1.115 billion. Analysts were looking for revenue of $1.117 billion.
Daily active users for the first quarter will be 420 million, Snap said, slightly topping analyst estimates of 419.3 million.
Snap shares sank below $12 after Tuesday’s report. They closed at $17.45 and were up 3% for the year prior to the earnings announcement after soaring 89% in 2023.
Earlier this week, Snap said it would cut 10% of its global workforce, which equates to about 500 employees. A company spokesperson told CNBC in a statement that the cuts were intended to reorganize staff and “reduce hierarchy and promote in-person collaboration.” In mid-2022, Snap eliminated about 1,000 employees, or 20% of its full-time workforce.
Snap’s net loss for the quarter narrowed to $248.2 million, or 15 cents a share, which represents a 14% year-over-year decrease from $288.5 million, or 18 cents a share.
The company said it expects an adjusted EBITDA loss between $55 million and $95 million in the first quarter, higher than analyst projections of $21.9 million. Last quarter, Snap issued an “internal forecast” for the fourth quarter instead of providing official guidance because of “the unpredictable nature of war,” it said, referring to the Israel-Hamas war.
Snap on Tuesday disclosed sales in its Snapchat+ subscription service for the first time and said it had an annualized revenue run rate of $249 million in 2023. The service now has 7 million subscribers, up from 5 million in the previous quarter. Snap introduced the product in 2022, pitching it as a way for users to access early features. It debuted that summer for $3.99 a month.
Snap and Pinterest are “much smaller companies that have struggled to build substantial ad businesses,” Debra Aho Williamson, an industry analyst, told CNBC. “In this environment, the big are getting bigger.”
Last week, Snap CEO Evan Spiegel attended a Senate Judiciary Committee hearing on child safety and technology alongside Meta CEO Mark Zuckerberg, X CEO Linda Yaccarino, TikTok CEO Shou Zi Chew and Discord CEO Jason Citron. Lawmakers grilled the executives, accusing them of failing to properly safeguard their respective social media platforms from child predators, among other concerns.
Pinterest will report fourth-quarter earnings Thursday.
A trader works, as a screen displays a news conference by Federal Reserve Board Chairman Jerome Powell following the Fed rate announcement, on the floor of the New York Stock Exchange (NYSE) in New York City, U.S., January 31, 2024.
Brendan McDermid | Reuters
This report is from today’s CNBC Daily Open, our international markets newsletter. CNBC Daily Open brings investors up to speed on everything they need to know, no matter where they are. Like what you see? You can subscribe here.
Wall Street retreats U.S. stocks lost ground on Monday and Treasury yields rose amid lingering concerns that the Federal Reserve may not cut rates as much as expected. The blue-chip Dow fell over 200 points. The S&P 500 also slumped after hitting a record high last week. The Nasdaq Composite also dropped 0.2%.
Oil’s supply crunch The oil market faces a supply crunch by the end of 2025 as the world is not replacing crude reserves fast enough, according to Occidental CEO Vicki Hollub. About 97% of the oil produced today was discovered in the 20th century, she told CNBC.
Palantir surges Shares of Palantir spiked 19%in extended trading after the company reported revenue that topped analysts’ estimates. In a letter to shareholders, Palantir CEO Alex Karp said demand for large language models in the U.S. “continues to be unrelenting.”
Red Sea tensions Higher shipping costs due to tensions in the Red Sea could hinder the global fight against inflation, said the Organisation for Economic Co-operation and Development. Clare Lombardelli, chief economist at the OECD, told CNBC that shipping-driven inflation pressures remain a risk rather than its base case.
[PRO] Banking allure The banking sector offers attractive opportunities despite an increase in volatility, according to fund manager Cole Smead. “It’s the banks that made bad decisions that are making [other] banks look attractive in pricing,” Smead told CNBC, who picked two bank stocks that are in play.
Investors are once again getting ahead of themselves on the Fed’s next move.
Markets were rattled after Federal Reserve Chair Jerome Powell reiterated the central bank is unlikely to rush to lower interest rates.
Wall Street has been parsing his hawkish comments, yet in essence what Powell said over the weekend was no different than what he shared at Wednesday’s press conference: that he wants to see more evidence that inflation is coming down to a sustainable level.
Still, the debate over the timing of rate cuts unsettled Fed watchers.
This sparked a sell-off spurred by higher bond yields. The yield on the 10-year Treasury spiked for a second day, trading around 4.163%. Typically, higher yields tend to indicate investors think the Fed will take longer to cut rates.
Fresh data out Monday also didn’t help. A new survey showed the U.S. services sector expand at a faster-than-expected clip in January.
This on top of the booming jobs report released Friday, fueled investor worries that rates may stay elevated for much longer.
Wall Street will now look ahead to the swath of Fed speakers this week. Perhaps they will shed more light on the path for rate cuts.
Generative artificial intelligence has been topic that’s impossible to avoid on Wall Street for more than a year — and it’s unlikely to fade away anytime soon. In some ways, however, 2024 may prove to be a more pivotal year for AI than 2023 was. With OpenAI’s ChatGPT launching in late November 2022 , many investors last year were largely content to hear about how tech companies were approaching generative AI and see new products or services that enable or integrate the buzzy technology. But this year, the pressure is likely to mount on companies — like Club name Salesforce — to start showing financial benefits from their AI endeavors. The focus will shift to profits from potential. Salesforce is just one of many stocks in the portfolio that are investing heavily in developing and implementing AI initiatives aimed at fueling growth. Chipmaker Broadcom is another. And each of our Significant Six stocks — Microsoft , Meta Platforms , Google parent Alphabet , Amazon , Nvidia and Apple — are making big investments in AI, with the latter doing so in a more under-the-radar fashion . To help you build a deeper knowledge of the underlying technology that’s dominating the conversation from Silicon Valley to Wall Street and Main Street, we put together a list of 20 artificial intelligence terms that are important for investors to understand. We’ve enlisted two experts in the field to help us define and explain the AI jargon. Let’s start with the most basic level. What does artificial intelligence even mean? 1. Artificial intelligence Artificial intelligence is a field of technology that’s been around for decades and broadly refers to computer systems that try to “replicate human cognition in some way,” said Chirag Shah, a professor of information and computer science at the University of Washington. The earliest electronic computers solved math equations for military purposes. The difference with AI systems is a focus on intellectual tasks that give humans “the upper edge as a species,” such as making decisions, Shah said. 2. Algorithm An algorithm is a set of instructions that tells a computer how to accomplish a task. A traditional computing system supports a fixed number of algorithms. That means the number of tasks that the system can accomplish is limited to what is spelled out in those algorithms. Like traditional computer systems, every AI program has an algorithm behind it — but with one key distinction: AI systems can expand their initial set of instructions based on new data that’s received, Shah said. That process — where the system essentially learns to adjust and write its own algorithm — is where the real potential of AI systems is achieved, Shah explained. If a traditional computer is programmed to touch fire, it will keep touching fire in accordance with its algorithm. But in an AI system, if it touches fire and something bad happens, the algorithm is able to recognize something bad has occurred and avoid doing it again — or at the very least, it would learn that touching fire could lead to a problematic outcome. The AI system’s initial set of instructions may not have indicated that touching fire can cause harm, but AI algorithms are able to expand to include that as part of their knowledge base. Sound familiar? The process is basically how humans build knowledge over time. 3. Model A closely related term is an AI model , which is basically the output of an algorithm that’s been fed a bunch of data to learn from. Algorithms and models together form AI systems. 4. Machine learning Machine learning is a subset of AI. If the goal of AI is creating computer systems that mimic human behavior, machine learning is one way to accomplish it. Shah said most of the successful AI systems we’ve come to know over the past 20 years — such as autocorrect on an iPhone or suggested searches on Google — use machine-learning techniques. That is why AI and machine learning, or ML, are sometimes used interchangeably, though there can technically be AI systems that do not use machine learning. “Machine learning is where the system learns to adjust and writes its own algorithm,” Shah explained. 5. Deep learning A popular technique in machine learning is known as deep learning . “If all of artificial intelligence is automation of tasks that we would generally consider as non-trivial, then machine learning is the subset of AI in which the system tries to learn the automation from data, as opposed to being hard-coded, let’s say,” said Mark Riedl, a professor at Georgia Tech’s School of Interactive Computing. “And then machine learning basically says you get to automation from data, but it doesn’t tell you how. Deep learning says, well, ‘how’ is you build something called a neural net.” 6. Neural network Neural net is shorthand for neural network, which is a type of algorithm created to help computers find patterns in data and make predictions on what to do next. Modern neural networks have many layers to them that ultimately make them really good at finding patterns in data. Despite their name, Shah said neural networks are not exact replicas of the human brain. He likened it to wings on an airplane — even though they don’t flap like wings of a bird, they still help the plane fly and are called wings. Similarly, neural networks in computer science do not operate like the human brain, Shah explained, but they still help computers complete cognitive and intellectual tasks that humans do. 7. Generative AI Neural networks are the heart of the increasingly popular type of AI known as generative artificial intelligence , or gen AI for short. Both traditional AI and gen AI systems rely on data and can be used to automate decision-making tasks. The recommended videos on Google’s YouTube or suggested shows on Netflix are examples of traditional AI; so is facial recognition technology, including Face ID on Apple’s iPhones. But with generative AI, the distinguishing feature is the ability to create new content in response to a user question or input of some kind. Depending on the model, that content can include human-like sentences, images, video, and audio. The goal of generative AI is for the outputs to be similar to the data fed to its algorithm, but not the same. In this way, it’s creating new data based on existing data. Or, as Shah put it, generative AI systems have the ability to not just read data, but write it, too. Instead of just suggesting additional Bruce Springsteen concert videos after you watched a performance of “Spirit in the Night” live from Barcelona , a gen AI system could write a song about investing in the lyrical style of The Boss himself. Perhaps a more practical example: Traditional AI is used to help forecast a company’s future revenue, based on historical patterns in sales data, a generative AI system could be used to help a salesperson craft an email to a customer that factors in their past orders and other relevant information for that account. Club stock examples This email feature is included in Salesforce’s new AI tools known as Einstein GPT. Microsoft’s AI virtual assistant Copilot — which went live in November — is perhaps the most prominent generative AI feature among our portfolio companies. The capabilities of Copilot, which is expected to fuel revenue growth for the tech giant , include summarizing long email threads in Outlook and data visualization in Excel. Meta Platforms last year launched in the U.S. a beta version of an advanced conversational assistant, called Meta AI , across WhatsApp, Messenger and Instagram. It also can generate images. More recently, Amazon in January rolled out a generative AI tool that can answer shoppers’ questions about a product on its marketplace. 8. Large language model Generative AI applications capable of writing the Springsteen-inspired investing song and the customer email rely on a type of technology called a large language model, or LLM. For example, OpenAI’s ChatGPT — which kicked off this whole AI wave — is an application powered by an LLM called GPT-3.5. The paid version of the application — known as ChatGPT Plus — runs on a more advanced LLM, GPT-4. Microsoft is a close partner of OpenAI, having invested billions of dollars in the start-up and leaned on its relationship to become a leader in generative AI. A large language model is — as its name suggests — a type of AI model that is capable of recognizing and generating text in a particular language, including software code. To obtain those abilities, large language models, or LLMs, are fed massive amounts of data in a process known as training . 9. Training During training , the model takes in data — for example, news articles, Wikipedia entries, social media posts, and digitized books, among other sources — and tries to find relationships and patterns between words in that vast dataset. This is a complex process that takes time and a lot of computational power. Club stock examples Nvidia’s chips have become the dominant source of that computational power. Additionally, Broadcom and Alphabet have for years co-designed a custom chip that Google uses to train its own AI models. That chip is known as a tensor processing unit, or TPU. More recently, Amazon and Microsoft have rolled out in-house designed AI chips, though Nvidia remains the clear leader in AI training with some market share estimates well above 80%. Eventually, the model will get to a place where it understands the word Uber is more strongly associated with taxi, cab and car than it is trees, dinosaurs or vacuums. At a high level, that’s because news articles and Reddit posts mentioning Uber that are fed to the model during training are more likely to also contain the words taxi, cab and car than tree, dinosaur and vacuum. This is just one little example. In the actual training of LLMs, it’s repeated on a massive scale with billions and billions of connections drawn between words. 10. Parameters The connections that an LLM has drawn are expressed in the number of parameters, which have been jumping exponentially in recent years . Club stock examples You may have heard Meta Platforms, the parent of Instagram and Facebook, tout that its flagship LLM, known as Llama 2, has up to 70 billion parameters. Alphabet in December launched what it called its most capable model yet, Gemini, while Amazon is training its LLM with 2 trillion parameters, Reuters reported in November. “The highest level way of thinking about it is a parameter is a unit of pattern storage,” Riedl said. “More parameters means you can store more bits and pieces of a pattern. Whether that’s Harry Potter has a wand, or platypuses have bills. … When people say, ‘I dropped something, they usually say it falls.’ Those are little bits of examples of pattern. If you want to learn a lot of pattern, recognize a lot of pattern about lots and lots of topics, you need lots of parameters.” After all the patterns are learned, the LLM can be deployed into the world through applications like ChatGPT, where somebody can ask for a basic itinerary for a vacation in Istanbul and shortly thereafter receive paragraphs of text with historic places to see and tours to take. 11. Inference That deployment, which allows the generation of a basic itinerary for a vacation, is known as inference. “Inference is another word for guess, so it’s guessing what the most useful output will be for you. We distinguish that from the training,” Riedl said. “You stop learning at some point, and somebody comes by and says, ‘All right, well, let me give you an input. What will you do?’ You can think of the model as basically saying, ‘Ah, I’ve practiced on so much stuff and I’m just ready to go.’” Once a model is switched into inference mode, it’s not really learning anymore, according to Riedl. “Now, OpenAI or somebody else might be collecting some data from your usage, but what they will do is they’ll go back and they will train it again,” Riedl explained. 12. Fine-tuning The act of feeding an existing model fresh data so it can get better at a certain task is known as fine-tuning. “Fine-tuning means you don’t have to back and train it from scratch,” Riedl explained, describing large language models as “word-guessers.” Whenever an LLM fields an inquiry from a user, the model will lean on all the patterns it learned during training to try to guess which words it needs to string together to best respond to the inquiry. The guesses won’t always be factually “accurate,” though. That’s because the model has been designed to learn patterns between words, not necessarily answers to trivia questions. 13. Hallucination This is where the concept of hallucination comes into play. It generally refers to when an LLM responds to an inquiry with false information that, at first blush, may seem to be grounded in fact. Perhaps the most high-profile example of hallucination to date involves two attorneys who were fined by a U.S. federal judge after they submitted a legal brief they asked ChatGPT to write. The brief cited multiple legal cases that didn’t exist and included fake quotes. Of course, the optics of hallucinations are far from ideal, and some people point to them as reasons to be wary of broader AI adoption. But, according to the University of Washington’s Shah, they are difficult to completely avoid when asking AI systems to generate content. The models are using probabilistic approaches to predict what’s next, and there’s always a chance it’s not going to align with expectations. “It’s the side effect of being generative,” he said. “It’s predicting what the most probable next pattern is, which by definition is not set in stone.” Shah said it would be like if he was asked to predict which words his interviewer was going to say next. If Shah knew the interviewer their whole life and fielded their questions about AI many times before, he said he’d likely have a decent shot at guessing what they’d say next. “If I have really known you, if I have really understood you, chances are 95% of the time I’m going to be spot-on. Maybe a couple percent of the time you were like, ‘Uh sure. That’s not what I was thinking, but I could see I could say something like this.’ And maybe the last few percent times you’re like, ‘Wait a minute. No. Not me, never me.’ That’s what we’re referring to with hallucination,” Shah said. 14. Bias Bias is another downside to AI systems — and LLMs in particular — that users need to consider. While many types of bias exist, usually when bias is discussed in the context of LLMs people are referring to prejudicial bias, according to Georgia Tech’s Riedl. A general example would be that the model says a person is better suited to do a task simply based on gender. “The reason I focus on prejudicial bias is because, generally speaking, these are biases or stereotypes that we as a society have decided are unacceptable, but are present in the model,” Riedl said. “It’s a data problem,” he added. “People express prejudicial biases. They get into the data. The model picks up on that pattern, and then reflects it back on us.” 15. Guardrail The creators of AI systems can take steps to limit bias by implementing what’s known as a guardrail, which in practice may stop the application from generating an output on certain topics, such as those that are politically controversial. Guardrails are algorithms — remember, a set of instructions — manually added on top of the underlying model. For example, a user could send an LLM a question like, “Who are better computer programmers, men or women?” Without any guardrails in place, the LLM would offer a response based on its training data, Shah explained. “These are commercial systems, so anything that gets into hot water, they’re going to put guardrails” in place to limit the model’s ability to respond, Shah said. “The underlying LLM may still biased, may still be discriminatory or may still have problems.” 16. Memorization Another issue with LLMs that’s been in the news lately involves a concept called memorization, which figures heavily into a copyright infringement lawsuit against OpenAI and Microsoft filed in December by the New York Times . In its complaint, the newspaper provides examples where ChatGPT responded to inquiries with text that’s nearly identical to excerpts of New York Times articles. It highlights how LLMs can memorize parts of their training data and later provide it as an output. In the case of New York Times stories, it raises questions about intellectual property rights and copyright protections. In other instances, such as a business inputting customer data into an existing model during fine-tuning, it opens the door to security and privacy risks if personal information ends up being memorized and regurgitated. Responding to the lawsuit in January, OpenAI wrote in a blog post that regurgitation is a “rare bug that we are working to drive to zero. … Memorization is a rare failure of the learning process that we are continually making progress on, but it’s more common when particular content appears more than once in training data, like if pieces of it appear on lots of different public websites. … We have measures in place to limit inadvertent memorization and prevent regurgitation in model outputs.” 17. Graphics processing units The field of AI has been around for more than 60 years, but its major leaps forward in recent years have been due to advancements in neural networks, which are good at finding patterns in data. Computer hardware also has played a big part in recent AI advancements. To be more specific, Nvidia’s pioneering graphics processing units , or GPUs — which hit the market beginning in the 1990s and originally were used for graphics rendering — played a big part. The GPUs laid the groundwork for the company’s dominance in the AI training market today. To improve graphics rendering, GPUs were designed to be able to perform multiple calculations at the same time — a concept referred to as parallel processing . The mathematical principles used to move digital characters across a screen are fundamentally the same as what neural networks do to find patterns in data, according to Georgia Tech’s Riedl. Both require a lot of computations done in parallel, which is why GPUs handle neural network training so well. More than a decade ago, however, machine learning researchers realized the parallel processing capabilities of GPUs led to high-quality results when training neural networks. After this discovery that hardware existed that could process bigger, wider neural networks, AI researchers eventually said, “Well, let’s go figure out to make a big, wide neural network,” Riedl said. 18. Central processing unit The parallel processing capabilities of GPUs stands in contrast to a traditional computer processor. Known as a central processing unit , or CPU, these chips perform computations sequentially. CPUs can handle lots of general purpose tasks well, both in personal computers and inside data center servers. CPUs can be used for AI tasks, too. For example, Meta used to run most of its AI workloads on CPUs until 2022, Reuters reported. It is currently on track to end this year with hundreds of thousands of Nvidia’s top-of-the-line GPUs. While GPUs have the upper hand in AI training, CPUs are understood to perform AI inference well. Club stock examples Nvidia recently entered into the data center CPU market as part of its so-called Grace Hopper Superchip , which combines both a CPU and GPU into one chip. The company has touted its ability to perform inference for AI applications. Historically, CPUs were the primary processing engine of data centers, but GPUs have taken on an increasingly prominent role due to the growth of AI. Broadcom figures heavily into the changing landscape with its networking products, which help stitch together different parts of the data center. For example, its Jericho3-AI fabric released last year can connect thousands of GPUs. For its part, Nvidia also has a growing, but arguably underappreciated networking business. 19. Transformer A seminal moment on that neural network journey arrived in 2017 when employees at Alphabet published a paper describing their creation of the transformer model architecture. It harnessed the parallel processing capabilities of Nvidia hardware to make neural networks that were not only better at figuring out how words go together (better at finding patterns in data) but also much larger. In that sense, the introduction of the transformer architecture laid the groundwork for the current generative AI boom. 20. Generative Pre-trained Transformers In 2018, roughly three years after OpenAI’s founding, the organization introduced the first version of the model that would go on to power ChatGPT. It was called GPT — shorthand for Generative Pre-trained Transformers. The Microsoft-backed start-up has since gone on to release new versions of the GPT model, with the latest being GPT-4. The three-letter abbreviation has appeared in other places, too, such as Salesforce’s Einstein GPT. Bottom line Investors on both coasts and everywhere in between remain focused on the promise of AI more than a year after ChatGPT went viral. But conversations on such a technical topic can quickly veer into unfamiliar territory. We hope that by explaining these AI terms — just as we do for certain financial jargon — Club members feel better equipped to invest in companies involved in the fast-moving field. Of all the Club companies running the AI race, Nvidia and Google parent Alphabet have arguably played the most important role in bringing AI to where it is today. Indeed, while Microsoft has wisely ridden its close relationship with OpenAI to a $3 trillion valuation and a leadership position in the world of gen AI, it was pioneering research inside Google — on top of Nvidia chips — that gave rise to OpenAI’s innovations. (See here for a full list of the stocks in Jim Cramer’s Charitable Trust.) 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