Fed Stands Pat on Rates, Entering New Wait-and-See Phase Chair Jerome Powell says ‘We do not need to be in a hurry to adjust our policy stance’

(…) With interest rates now “significantly less restrictive” than they were before last year’s cuts, “we do not need to be in a hurry to adjust our policy stance,” said Fed Chair Jerome Powell at a news conference after the meeting.

Those comments suggested the central bank was likely to stay on hold at its next meeting in mid-March. Powell said the Fed would need to see “real progress on inflation” or unexpected weakness in the labor market before considering further rate reductions. (…)

“We seem to be set up for further progress” on inflation, he said. Being set up for progress is one thing, “but having it is another.” (…)

Minutes from the Fed’s previous meeting, released earlier this month, said a substantial majority of officials still judged their policy stance at the time to be “meaningfully restrictive.” (…)

John Authers:

Everyone knew that the Fed wouldn’t change interest rates. They also did nothing to change their policy of gradually reducing the balance sheet. Instead, the greatest excitement in its communique came from a slight alteration in language about inflation and unemployment. Last month, the FOMC statement said:

Labor market conditions have generally eased, and the unemployment rate has moved up but remains low. Inflation has made progress toward the Committee’s 2 percent objective but remains somewhat elevated.

This month that changed to:

The unemployment rate has stabilized at a low level in recent months, and labor market conditions remain solid. Inflation remains somewhat elevated.

So if the labor market is solid rather than easing, and the Fed no longer says it’s making progress toward the 2% target, that sounds like a distinct shift toward hawkishness — a propensity to make the next move a hike. Then Powell was asked about what appeared to be a critical signal in his Q&A. His response:

If you just look at the first paragraph, we did a little language cleanup there… We just chose to shorten that sentence.

(…) The effect of the Fed’s language cleanup — and Powell’s subsequent attempt to clean up how people had interpreted it — was clearly visible across broader financial markets. The dollar, the gold price, the 10-year Treasury yield, and the S&P 500 all moved sharply. Those moves were completely reversed on Powell’s clarification. In the final analysis, the Fed did a good job of convincing people that it wanted to cut rates, but was in no hurry to do so.

Bank of Canada Cuts Rates, Warns of Economic Shock From Trade Conflict Policy rate down quarter-point, officials warn of tricky balancing act with potential of weaker growth, higher prices

Bank of Canada Gov. Tiff Macklem said the central bank would be limited in offsetting the damage from a trade row, because policymakers would have to wrestle with both weaker growth and higher prices. The central bank sets interest rates to achieve and maintain 2% inflation.

The Bank of Canada can “try to be a source of stability” through a potential trade disruption, Macklem said, “so the adjustment is less unpleasant than it otherwise would be.” He added, “We can’t lean against weaker output and higher inflation at the same time.”

Canada’s central bank lowered its policy rate by a quarter-point to 3%, as widely expected in a survey of economists last week by The Wall Street Journal. In its decision, the Bank of Canada said a recent rebound, fueled by aggressive rate cuts since last June, is in jeopardy should President Trump follow through on his threat of a 25% tariff on imports from Canada and Mexico. Canadian officials have vowed to retaliate forcefully with their own tariffs in such an event.

“A long-lasting and broad-based trade conflict would badly hurt economic activity in Canada,” Macklem said. (…)

Roughly three quarters of all Canadian exports are U.S.-bound, and Trump has said the hefty tariffs could begin as early as Saturday.

Initially, Trump said the 25% tariff would be in place until Canada and Mexico fortified their border security. He has since expanded his reasoning, complaining about a trade deficit Canada runs with the U.S. (…)

The central bank, in its decision Wednesday, removed any guidance about the future direction of interest rates. At his press conference, Macklem outlined scenarios in which officials might either have to cut rates to support growth, or raise them to prevent one-time cost increases from tariffs from feeding into wages and other prices. (…)

Bank of Canada analysts modeled a scenario in which the U.S. imposed a 25% tariff on all imports, and its trading partners responded in kind, over a multiyear period. In that model, the trade row would knock down Canadian growth by 2.5 percentage points in the first year. As a result, the 1.8% growth forecast for Canada this year would turn into a decline of 0.8%, or a recession. (…)

The central bank published a quarterly forecast. Absent tariffs, the Bank of Canada expects 1.8% growth in both 2025 and 2026, or a downgrade from the previous forecast of 2.1% and 2.3% respectively. Officials attribute the downward revision to a projected slowdown in population growth stemming from immigration-policy changes.

Hiring has picked up, although Macklem said the labor market remains soft and there are indications wage growth is easing.

AI CORNER

Microsoft, Meta Talk Up Their Big AI Ambitions and Spending Plans Tech giants vow to barrel ahead despite jolt from China’s DeepSeek

(…) Microsoft Chief Executive Satya Nadella and Meta CEO Mark Zuckerberg said in earnings calls that DeepSeek had made real innovations. But the two portrayed the Chinese company’s work as part of a technological evolution that will make AI cheaper and more widely used rather than the extensive disruption that some observers have perceived.

“There’s a number of novel things that they did that I think we’re still digesting,” Zuckerberg said on a call with analysts after Meta reported record quarterly sales and strong profit growth. “I continue to think that investing very heavily in [capital expenditures and infrastructure] is going to be a strategic advantage over time. It’s possible that we’ll learn otherwise at some point. But I just think it’s way too early to call.” (…)

“In some sense what’s happening with AI it’s no different than what was happening with the regular compute cycle. It’s always about bending the [cost] curve,” Nadella said. (…)

Wednesday he said simply that “as AI becomes more efficient and accessible, we will see exponentially more demand.” (…)

Zuckerberg on Wednesday emphasized that the winners of the AI arms race—both countries and companies—will be able to set the terms.

“There’s going to be an open-source standard globally,” he said on Meta’s earnings call in response to a question about DeepSeek. “For our, kind of, own national advantage, it’s important that it’s an American standard,” he said. “So we take that seriously and we want to build the AI system that people around the world are using.”

Zuckerberg said DeepSeek did “a number of novel things” that Meta hopes to implement in its systems. (…)

He predicted that companies investing vast sums in computing infrastructure will be able to deploy it in ways that can adjust as AI advances, and such investments will continue to be an advantage. More computing power can generate a higher level of intelligence and service, he said. (…)

“People don’t all want to use the same AI,” he said. “People want their AI to be personalized to their context, their interests, their personality, their culture, how they think about the world.”

Microsoft said it expects the next two quarters to be similar to the $22.6 billion it spent in the last quarter, which is roughly in line with Wall Street’s expectations. The company didn’t say if DeepSeek’s breakthroughs would eventually lead to a big reduction in spending on AI computing—the key fear driving Nvidia’s selloff.

• U.S. Businesses Already Love DeepSeek The Chinese company’s new model promises to lower the cost of AI for enterprises—even amid concerns about cybersecurity and geopolitics

(…) New York Life Chief Data and Analytics Officer Don Vu said the insurance company is exploring the use of DeepSeek’s AI model. Vu said the company has a framework for evaluating the effectiveness of different models, like OpenAI’s GPT, Anthropic’s Claude and Meta Platforms’ Llama, for different use cases. It will now test how effective DeepSeek’s new model is in areas such as service and claims.

What New York Life won’t be doing, Vu said, is using the existing DeepSeek app, which raises data security questions. It will instead download the open-source version and begin experimenting with that.

For security reasons as well as ease of use, some enterprises will prefer not to host their own versions of the DeepSeek model and will turn to vendors like Amazon that make them available through their platforms. Smaller versions of new DeepSeek models are now available on Amazon Bedrock, the company’s AI development platform, for enterprises to test, run and use for business cases, a company spokesperson said.

German software company SAP said it is open to leveraging AI models coming from Chinese companies like DeepSeek if they meet certain cost, reliability and data privacy requirements, its Chief Financial Officer Dominik Asam told The Wall Street Journal. (…)

The Chinese ownership is a clear deterrent for some CIOs who might otherwise consider leveraging the tech, even as they remain optimistic about the pressures it could put on U.S. tech companies.

Marc Kermisch, chief technology officer of Emergent Software, said tech leaders should consider blocking the app for overzealous employees who might inadvertently put corporate data into it, although he said he is experimenting with it in a controlled environment. Given its Chinese ownership, Kermisch said he is skeptical that DeepSeek’s model will become viable for widespread use by American companies. But he said he is still hoping it can take a role in pressuring U.S. model makers to drive down costs. (…)

Brian Greenberg, CIO of leadership consulting firm RHR International, said he considers DeepSeek’s new model “fascinating and worthy of exploration.” However, that excitement should be tempered. To use the open-source version of DeepSeek inside the company, Greenberg added, would require a strict cybersecurity review.

Adnan Masood, chief AI architect of digital technology and information-technology services firm UST, said, “The anxiety is that you’re feeding sensitive corporate data into a system that originated from a strategic adversary, no matter how ingenious the engineering.”

“On the flip side, drastically lower costs and advanced capabilities tempt executives to risk these concerns for competitive advantage,” he added.

• It’s Not Just DeepSeek. A Guide to the Chinese AI Companies You Need to Know. Chinese internet giants and startups are competing with each other and U.S. rivals

Alibaba: The e-commerce giant provides conversational chatbot service Qwen, powered by multiple AI models, including some designed for more complex reasoning and coding tasks. This week, it also released Qwen2.5-Max, an artificial-intelligence model it said was competitive with global leaders, including DeepSeek. It hasn’t clarified whether it developed the model with the low cost and high efficiency that DeepSeek has boasted of.

Tencent: China’s biggest videogame company has developed multiple versions of its AI model Hunyuan. It said one version released in November delivered performance comparable to Meta’s Llama 3.1. According to some researchers, Tencent might use around a tenth of the computing power Meta used to train the model. The company is integrating AI capabilities into its WeChat app, the ubiquitous platform in China providing everything from chats to banking.

Baidu: Baidu, which first emerged as a search-engine company, was the first in China to launch a ChatGPT equivalent, called Ernie Bot. Its technology chief said in November that its model had 430 million users.

ByteDance: The owner of TikTok has a chatbot called Doubao, which can be translated as bean bun. The app has been among the most downloaded chatbots in China, with around 60 million monthly active users, according to Aicpb.com, a website tracking AI products.

DeepSeek: The company surprised the global tech community earlier this month after it said it had trained AI models that delivered high performance at low cost and without the most advanced chips. Then, on Tuesday, it released a multimodal model, called Janus Pro, that it said could produce results comparable to OpenAI’s text-to-image model DALL·E 3.

StepFun: The company, valued at around $2 billion, has a model that is now ranked for performance among the top 10 in the world in Chatbot Arena. Founded by a former senior Microsoft scientist, the company counts Tencent and the Shanghai government as key investors.

Moonshot AI: Moonshot’s Kimi chatbot has around 13 million users in China, according to Aicpb.com. The startup, valued at around $3.3 billion and backed by Alibaba and Tencent, was founded by a young Chinese scientist who had stints at Meta and Google. This month, Moonshot released a multimodal reasoning model, called k1.5, that it said outperformed big names such as OpenAI’s GPT-4o and Anthropic’s Claude3.5 Sonnet on some major benchmarks, including a math challenge.

MiniMax: MiniMax is a Shanghai-based startup valued at $3 billion. It invented a Character.ai-like companion chatbot called Talkie, which has become popular in the U.S. This month, it published two open-source models that it claimed to be comparable to OpenAI’s GPT-4o and Anthropic’s Claude3.5 Sonnet, using a technique called Lightning Attention that allows faster computation.

Zhipu: Zhipu, valued at around $3 billion in its latest fundraising round in December, has invented a chatbot, as well as a video-generating model called Ying that is similar to OpenAI’s Sora. Zhipu was also included this month in a U.S. trade blacklist for developing AI systems that could have military uses. Zhipu said the U.S. move was baseless.

• DeepSeek’s ‘Open AI’ Should Terrify Sam Altman It’s not the only company building systems that are free to use.

(…) Across the world, similar open-source models are being built, ready to eat into Altman’s market share with systems that are vastly cheaper or even free to use. That’s an unnerving prospect for businesses like OpenAI and Anthropic, whose primary path to profitability is selling access to a foundation model for a higher price. (Alphabet Inc.’s Google and Microsoft Corp. at least have cloud and software businesses to fall back on.) Publicly available models like DeepSeek might not reign supreme in the end, but they could win an uncomfortably large share of the pie, and fulfill promises1 that Altman has neglected around openness and collaboration.

“DeepSeek’s paper on [its new AI model known as] R1 was more transparent than anything I’ve seen from OpenAI since GPT-3,” says Gary Marcus, a professor emeritus at New York University, who has long bemoaned OpenAI’s opacity and warned of an AI market crash.

That openness is part of a shift happening in China. (…) The Chinese company has put most of the details about R1 on the internet, something that OpenAI and Google wouldn’t do today. Its breakthrough is essentially a novel approach to so-called reward modeling, according to one summary of the findings.

(…) DeepSeek isn’t technically “open source,” according to the Open Source Initiative (OSI), a global authority that certifies software licenses. “They do not provide the source code to process and filter and train the data, nor the information about the training data,” a spokesman for the OSI tells me. “Others would have to build this from scratch based solely on the paper they published.”

But as a so-called open-weight system, DeepSeek can still provide the crucial model parameters that others can copy and improve upon, unlike OpenAI, which keeps its models locked in a black box. (…)

China’s shift toward building open-source models has come about in the last few years, driven by US export controls, government support and the impact of Meta’s own open-weights model, Llama, which several Chinese tech firms have been enthusiastically fine-tuning for their own applications, according to Computer Weekly.

For the entrenched giants of Silicon Valley, the real threat isn’t just China, but the way Chinese tech firms could fuel even greater momentum for the open-source movement in other parts of the world — like France, home to promising open-source AI firms Mistral AI and Hugging Face Inc., and the US, where research collective EleutherAI has been influential in creating models like GPT-J and GPT-NeoX.

Of course, open-source AI has downsides, the obvious one being misuse by bad actors. And while DeepSeek’s new model has solved the problem of cost, it hasn’t solved hallucinations. Plenty of examples exist on social media of users jailbreaking R1 to get around its Chinese Communist Party-friendly filters. And while the model was cheap to build, it is still relatively expensive to run, Marcus points out.

Yet DeepSeek is still giving open-source AI newfound credibility among software builders. Developers on forums like X have been showing off all the apps they’re building on DeepSeek’s free platform. (…)

OpenAI’s business of building foundation models has become commoditized. The real economic potential is for those building products on top of all that infrastructure, or on top of platforms like DeepSeek’s that are free to use.

The irony is rich. When OpenAI launched in 2015, it promised to “freely collaborate” and share its patents with the world. Instead, in its galactically ambitious quest for human-level AI, it began morphing into exactly what it set out to disrupt: an opaque, money-hungry tech giant, which is now being challenged by genuinely open AI.

Altman convinced the world that building powerful AI required massive resources, but he’s now learning that his moat isn’t that deep after all. Perhaps the future belongs not to those who can spend the most, but to those who dare to share their workings with the world.

FYI: The Most Important Time in History Is Now AGI Is Coming Sooner Due to o3, DeepSeek, and Other Cutting-Edge AI Developments

AI CORNER

The new Sputnik moment

Gavekal’s Louis-Vincent Gave reminds us that China was already ahead of the West on 5G, high-speed rail, solar panels, EVs, batteries, drones and robots, before the revelations of the competitive open source DeepSeek model.

(…) It now looks as if the hundreds of billions spent by the giants of US tech is essentially so much capital that will never see any returns—the “metaverse” fiasco all over again, only larger.

This marks an important shift in market narratives. Essentially, DeepSeek has taken a hot needle to the AI bubble, and the air will now be leaking out. This possibility raises the question whether the deflation of the AI bubble will remain a concentrated market phenomenon, with names like Nvidia coming back down to earth in isolation, or whether it will impact the broader market, with a lower Nasdaq, a weaker US dollar and stronger US treasuries.

In recent weeks, I have been showing the chart below to illustrate what an odd bull market US growth stocks have been enjoying. The outperformance of US growth stocks started in 2007, at a time when valuations had been thoroughly rinsed out. This bull market initially had two important drivers: the launch of the first Apple smartphone and the US shale revolution, which meant that the US suddenly had a cheaper cost of energy than almost everyone else and was set to record an improvement in its trade balance.

By 2015, investors realized that returns from investments in US energy would most likely disappoint, and the markets suffered a bit of a hiccup. But the combination of the “Shanghai agreement” with the promise of deregulation and Trump’s first-term tax cuts got things going again.

By 2020, the market had entered a typical “blow-off phase,” characterized by sheer silliness: the GameStop saga, the AMC stock surges, exercise bikes with iPads trading at a market cap of US$49bn, Metaverse spending etc.

Then, in 2022, the air came out of a lot of the flimsiest ideas and the more egregious Ponzi schemes, and the market rolled over. So far, the bull market was thoroughly “text book”: 10 years of solid outperformance, a couple of years of exuberance, then the implosion.

What was not textbook was the back-to-back very strong years in 2023 and 2024. These two years of impressive returns led by a handful of mega-cap stocks left the broad market indexes more concentrated than at any time in history. And the catalyst for this rebound? The release of ChatGPT and the sudden excitement over all things AI-related.

In truth, not much was textbook since 2008. Remember Bernanke’s ZIRP, helicopter money, the financial repression, COVID-19 and the mega handouts, core CPI surging from 1.2% to 6.6% and 10Y Ts at 1.5% while inflation was 3.2%.

And, BTW, a 50% jump in S&P 500 earnings between 2019 and 2024.

Also true: the increase in the trailing P/E from 19.8 in December 2019 to 25.1x currently.

Louis Gave continues (my emphasis):

All of which brings me back to the release of DeepSeek, and the following questions.

1.
Has AI reached a dot-com moment? At the end of the 1990s, hundreds of e-commerce platforms were funded by eager VCs. When Pets.com and others started to fail in 2000, and dot-com companies started to run out of money, companies like Lucent and Sun Microsystems that had extended credit to fast-growing customers suddenly found themselves in deep trouble on two fronts. First, their former clients were fire-selling their new equipment for cents on the dollar. Second, the clients stopped making the payments they owed. Balance sheets and income statements came under assault at the same time. Could history repeat, but this time with failing VC-funded AI companies selling the high-priced chips they were rushing to buy just months before on the fear of shortages?

2.
If the AI bull market stalls, what will take over? There are plenty of other exciting stories today: the rise of autonomous driving, Chinese stimulus, US deregulation, the impact of steeper yield curves on financials. Some of these themes center on the US. Others less so.

3.
If the next “new new thing” is not in the US, what will it mean for the US dollar? Last week the US dollar gave back some of its recent gains. Arguably, the US dollar’s rollover was linked to Trump’s softening stance on tariffs. But given the news on DeepSeek, it may not be all that surprising. If China can develop a more efficient AI at very low cost, it calls into question a lot of the recent rhetoric about the need for very high-end chips, one key US comparative advantage. Whatever the reason, the fact remains that over the past year, the US dollar and US growth stock relative performance have been heavily correlated. So if, as seems likely, the Nasdaq now starts to underperform on the back of the DeepSeek news, then given recent trends, the US dollar will most likely follow.

In closing, I would like to highlight that one of the odd things about the AI bull market has been its capital intensity. Up until a couple of years ago, one of the main attractions of tech companies (along with strong growth) was the “capital-light” nature of their business models. But AI turned this on its head. All of a sudden, the market seemed keen to buy semiconductor companies on triple-digit multiples, based on the premise that the tech world would now have a capital intensity higher than a steel plant or an oil refiner.

On the positive side, DeepSeek seems to bring things back to what tech should be: open-source and capital-light. This is ironic since it is coming out of China, where the popular perception is that growth is always capital-intensive and policy is anything but open-source!

Perhaps most importantly, DeepSeek destroys the idea that although having a few tech titans controlling the broader tech ecosystem might be socially pernicious, at least it makes for technological progress and ensures that the US remains technologically dominant. In this latest Sputnik moment, the tech war between China and the US, between open-source and closed-system, and between capital-light and capital-intensive models has just taken a very interesting turn.

Also likely to help:

• continued strong economic growth, particularly in the U.S.;
• +11.6% growth in earnings of S&P 500 companies ex-Tech and Comm. Services, per the current consensus, critically important in the current environment;
• lower personal and corporate tax rates in the U.S.;

Potentially offsetting: tariffs, higher deficits and a volatile U.S. president.

Louis’ point on private company debt gets support from this S&P Global’s chart showing deteriorating coverage ratios:

Bloomberg had this on January 11:

The International Monetary Fund is planning a deep dive on the growing prevalence of payment-in-kind debt that allows companies to defer interest payments, amid wider fears the tool could undermine financial stability by obscuring stress.

The watchdog plans to look at how often the expensive debt used to keep struggling companies alive is in fact merely delaying an inevitable insolvency, according to a person with knowledge of the matter. The IMF also plans to look at interconnections between banks and private credit after a series of lending partnerships were announced this year, the person added, asking not to be identified as they weren’t authorized to speak publicly.

Watchdogs across the world are concerned about the risk of bubbles in private markets against a backdrop of inflated asset values, high interest rates, and a rush-for-cash among firms battling to build scale. PIK has become an increasing area of focus, sweeping to prominence as private equity firms sought ways to manage higher-than-expected interest payments amid a prolonged period of higher rates.

The IMF work comes amid rising concerns about potential systemic risk from private credit’s growth. Of particular interest to the watchdog, the person said, is understanding the different layers of leverage in the financial ecosystem. Investors might borrow to help fund their allocations to private credit funds, which in turn might have leverage on their portfolios. And ultimately the money is flowing to companies getting loans from these funds. (…)

This is happening while valuations are

Unanimously Expensive: And here’s another angle on it, this one shows what looks to be the average historical percentile ranking across 8 different valuation metrics, and the signal is unanimous: the US stockmarket has reached new heights of valuation extremes. You can kind of explain away some of this with datapoints of how valuations don’t matter in the short-run, or that it’s expensive for good reason, etc, but I think it’s quite dangerous to try and argue that valuations don’t matter when we’re at this stage of the cycle (and it might even be outright irresponsible). (Callum Thomas)

Source:  @joosteninvestor via DailyShot

• “Consumers’ stock market bullishness remained near a record high in January according to the CCI survey. From a contrarian perspective, this is bearish. The “stock prices higher in 12 months” series is correlated with the S&P 500’s forward P/E, which is historically high. Nevertheless, we believe that better-than-expected earnings will drive the market higher, not rising valuations.” (Ed Yardeni)

BTW:

The GDPNow model estimate for real GDP growth (seasonally adjusted annual rate) in the fourth quarter of 2024 is 3.2 percent on January 28, up from 3.0 percent on January 17. After recent releases from the US Census Bureau and the National Association of Realtors, the nowcast of fourth-quarter real gross private domestic investment growth increased from -0.9 percent to 0.1 percent.

As I wrote previously, there is more than DeepSeek:

Alibaba Touts New AI Model Superior to DeepSeek’s and Meta’s

Alibaba Group Holding Ltd. published benchmark scores and touted what it called world-leading performance with its new artificial intelligence model release.

The upgraded Qwen 2.5 Max edition scored better than Meta Platforms Inc.’s Llama and DeepSeek’s V3 model in various tests, according to figures in Alibaba Cloud’s announcement on WeChat. Alongside Tencent Holdings Ltd. and Baidu Inc., Alibaba has poured significant resources into its cloud services segment and is engaged in a hot contest to recruit China’s AI developers to use its tools. (…)

Cloud service providers like Alibaba and Tencent have slashed their pricing in recent months in the effort to win over more users. DeepSeek has already contributed to that price war, alongside a half dozen other promising AI startups in China that have secured funding at unicorn valuations.

US Core Business Equipment Orders Increase by More Than Forecast Bookings for core capital goods ex-aircraft, defense rise 0.5%

Core capital goods orders, a proxy for investment in equipment that excludes often-volatile aircraft and military hardware bookings, increased 0.5% last month after an upwardly revised 0.9% increase in November.

Core capital goods shipments, a figure that excludes often-volatile sales of military equipment and commercial aircraft, increased 0.6% in December — the most in nearly a year. The latest figures will help economists fine-tune their business equipment spending estimates for fourth-quarter gross domestic product. Those figures will be reported on Thursday.

Including aircraft, shipments of nondefense capital goods jumped 3.5%. (…)

• “November’s surge in capital expenditures continued last month, with the 3-month moving average rising at the fastest pace in over two years, marking a 28-month high.” (Interactive Brokers)

Why the gap between new orders and production?

Imports?

• “All of January’s business surveys conducted by five of the 12 regional Federal Reserve Banks are now available. They strongly suggest that the month’s M-PMI was solidly above 50.0 for the first time since early 2022.” (Ed Yardeni)