Month: January 2025

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)

Trump Vows Tariffs ‘Much Bigger’ Than 2.5% and on Key Areas Trump says he wants universal levy to “protect our country”

“I have it in my mind what it’s going to be but I won’t be setting it yet, but it’ll be enough to protect our country,” Trump told reporters Monday night.

Asked about a report that incoming Treasury Secretary Scott Bessent favored starting with a global rate of 2.5%, Trump said he didn’t think Bessent supported that and wouldn’t favor it himself. He said he wanted a rate “much bigger” than 2.5%.

Trump spoke aboard Air Force One while he flew back to Washington, DC, from a Florida speech where he also pledged tariffs on specific sectors, including semiconductors, pharmaceuticals, steel, copper and aluminum. He also strongly suggested he could also impose them on automobiles from Canada and Mexico, countries he’s already threatened with 25% across-the board tariffs as soon as Feb. 1. (…)

“Remember, again, the word ‘tariff.’ We’re going to protect our people and our businesses, and we’re going to protect our country, with tariffs,” Trump added. He’s said to have earlier mused about tariffs of up to 20%. (…)

He repeated a call for Republicans to cut the corporate tax rate to 15%, from the current 21%, for companies that make their goods in America. (…)

Trump singled out several sectors in his speech to lawmakers. He complained at length about auto imports both from Canada and Mexico.

“They send us millions of cars; we don’t need them for that,” he said of Canada, America’s top export market. “We want to have the cars made in Detroit or South Carolina or many other locations.” Trump then added: “The auto workers voted for me and I have an obligation to do what’s right, and I’m going to do that.”

He sang the praises of steel tariffs that he implemented in his first term and said he’d be “placing tariffs on steel, aluminum and copper and things that we need for our military,” without elaborating. “We have to bring production back to our country.” (…)

BTW:

The heavy-handed tariff and financial sanctions threats, which would have been devastating for Colombia if imposed, also run a strategic risk: spurring other countries to look at the US threat of economic punishment and deciding to diversify toward non-US trade partners and payment systems, said Josh Lipsky, senior director of the GeoEconomics Center at the Atlantic Council.

While the US is historically Colombia’s top trade partner, Petro has already been strengthening ties with China. During the period on Sunday when US tariffs looked imminent, Petro called for deepening his nation’s connections with other markets. Having seen Colombia’s experience, other countries may follow suit.

“You have to wonder if there’s a Pyrrhic victory here, because the more countries see this threat, the more they start turning and looking at ways that they can diversify their own trading relationships,” Lipsky said. “There is a cost long term to the overuse of the threat. I think they broadly got the result they wanted here, but I do think there’ll be more cost throughout the region in the months to come.” (Bloomberg)

Already happening in Europe, Mexico and Canada. Every country now needs to examine how to reduce dependance on the USA.

The FT reminds us that “China has hugely expanded its trade and investment in Latin America this century, and Beijing is likely to view Trump’s unpredictable moves as an ideal opportunity to present itself as a more reliable partner, diplomats and analysts said. Shifter, of Inter-American Dialogue, said: “Celac is the platform for China in Latin America, so Thursday’s summit is a kind of proxy for showing [Washington] that if [it is] really going to punish us, then China’s willing to fill the gap and come in even more than it has already.”

AI CORNER

The DeepSeek AI Freakout The Chinese startup’s model stuns Big Tech—and Wall Street—with its capability and cost.

The WSJ Editorial Board:

(…) DeepSeek required far fewer chips to train than other advanced AI models and thus cost only an estimated $5.6 million to develop. Other advanced models cost in the neighborhood of $1 billion. Venture capitalist Marc Andreessen called it “AI’s Sputnik moment,” and he may be right.

DeepSeek is challenging assumptions about the computing power and spending needed for AI advances. (…)

CEO Mark Zuckerberg on Friday said Meta would spend about $65 billion on AI projects this year and build a data center “so large that it would cover a significant part of Manhattan.” Meta expects to have 1.3 million advanced chips by the end of this year. DeepSeek’s model reportedly required as few as 10,000 to develop.

DeepSeek’s breakthrough means these tech giants may not have to spend as much to train their AI models. But it also means these firms, notably Google’s DeepMind, might lose their first-mover, technological edge. Google shares fell 4% on Monday. DeepSeek’s model is open-source, meaning that other developers can inspect and fiddle with its code and build their own applications with it.

This could help give more small businesses access to AI tools at a fraction of the cost of closed-source models like OpenAI and Anthropic, which Amazon has backed. There are advantages to such closed-source systems, especially for privacy and national security. But open-source can foster more collaboration and experimentation.

It’s notable that DeepSeek is a startup founded by Liang Wenfeng, a Chinese hedge fund trader. Americans think of China’s economy as run top-down, and much of it is. But its growth over the last few decades, especially in tech, has been spurred by entrepreneurs. Alibaba, Tencent and ByteDance were all once startups that now rival U.S. tech giants. (…)

DeepSeek should also cause Republicans in Washington to rethink their antitrust obsessions with big tech. Bureaucrats aren’t capable of overseeing thousands of AI models, and more regulation would slow innovation and make it harder for U.S. companies to compete with China. As DeepSeek shows, it’s possible for a David to compete with the Goliaths. Let a thousand American AI flowers bloom.

• DeepSeek Undercuts Belief That Chip-Hungry U.S. Players Will Win AI Race More AI competition will make it hard for Big Tech to generate the oligopoly-like profit margins that investors hope for

(…) Monday’s AI crash was led by the first part, the “chips and shovels” that supported the development of AI, not the developers of these fancy programs themselves. Nvidia stock was down 17%, losing more than half a trillion dollars of value, nuclear-power stocks Constellation Energy, Vistra, Oklo and NuScale Power were down 21%-28%, and data-center supplier Vertiv Holdings was off 30%. (…)

The moves in prices appear to show investors focused on fundamental issues of how DeepSeek’s approach will lead to lower power use and less demand for chips and data centers. (…)

A lot of what’s been going on is similar to when investors discovered the internet. They have grasped that AI is A Big Deal, but can’t yet see exactly how or when it will make money. (…)

What are the prospects for Microsoft-backed OpenAI, Alphabet, Amazon-backed Anthropic, Elon Musk’s xAI and all the others to make money when faced with a low-cost competitor? DeepSeek is, after all, available, like Meta’s Llama, to download and tweak free.

On Monday this wasn’t the main concern, with Microsoft off 2.1%, Alphabet 4.2% and Amazon slightly up. They have big, profitable businesses they are using to finance AI development, and will also be able to use the techniques DeepSeek shared to lower their own costs. But they just lost one of the biggest barriers to entry. If a new AI model can be produced for just a few million dollars by the tech arm of a Chinese hedge fund, maybe others can do the same. (…)

Investors have been encouraging companies to pour cash into building new data centers, power stations and anything related to the power grid for the past year. Monday’s price drops suggest less appetite for real-world investments and could persuade companies to invest less into such projects. (…)

• DeepSeek Won’t Sink U.S. AI Titans Panic fueling the selloff of Nvidia, Broadcom and other tech giants is overblown

(…) The high entry price of AI—and sanctions from the U.S. government limiting the sale of advanced AI chips to Chinese companies—also serve as a competitive moat for tech titans such as Microsoft , Amazon, Google and Meta Platforms. They are among the few companies with enough capital to build out expensive AI networks on a large scale. (…)

The selloff seems excessive. Much remains unknown about DeepSeek’s claims, including what sorts of chips the company had access to despite the effect of sanctions. Several chip analysts on Monday disputed the notion that DeepSeek built something on par with advanced U.S.-based AI models at such a low cost.

“DeepSeek DID NOT ‘build OpenAI for $5 million,’ ” wrote Stacy Rasgon of Bernstein. “The ‘DeepSeek’ moment is driving investors to shoot first and ask questions later,” wrote Joshua Buchalter of TD Cowen. “While DeepSeek’s achievement could be groundbreaking, we question the notion that its feats were done without the use of advanced GPUs to fine tune it,” wrote Atif Malik of Citigroup.

More important, such a technical breakthrough is unlikely to cool the AI race or even cut down the funds being poured into it. Addressing the comparison of DeepSeek to Sputnik, Edward Yang of Oppenheimer said the Space Race didn’t result in less money going out the door. “Increased competition rarely reduces aggregate spending,” he wrote in a note to clients. Pierre Ferragu of New Street Research noted that more advanced “frontier models” will still need to push the technical edge and use the most advanced computing resources, while smaller “lagging edge” models will push to develop more cost-efficient AI features. 

“DeepSeek is not a game changer, and on the contrary fits very well with the way we have seen the industry evolving in the last three years,” Ferragu wrote. (…)

Microsoft, which reports quarterly results on Wednesday, will be the first big tech company with the opportunity to signal whether DeepSeek’s breakthrough will deep-six its investment plans. The company is expected to drop about $84 billion in capital spending for the fiscal year ending in June and $94 billion in the next year, according to consensus estimates from Visible Alpha. (…)

“As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can’t get enough of,” wrote Microsoft CEO Satya Nadella in a post on X on Monday morning.

The AI spending war might just be entering a new phase.

Not a game changer?

Almost overnight, DeepSeek has upended many of the assumptions inside Silicon Valley about the economics of building AI, as well as the best technical methods for developing the technology and the extent of the US lead over competitors in China. For much of the past two-plus years since ChatGPT kicked off the global AI frenzy, the industry has bet that the path to better AI depends largely on spending heavily on more advanced chips from companies like Nvidia Corp. and increasingly massive data centers to house them. (…)

“It’s a paradigm shift,” said Ali Ghodsi, CEO of Databricks Inc. “These models that can reason are so much cheaper to produce that you will see it be democratized. You’ll see innovations from unexpected corners of the world.” (…)

Like some of the latest models from OpenAI, Google and Anthropic, R1 is intended to parrot the ways humans sometimes ruminate over problems by spending time computing an answer before responding to user queries. DeepSeek’s version differs, however, in its efficiency. The team behind it came up with some simple but key innovations, such as finding ways to get more use from the computer chips they did have access to. Another breakthrough: leaning heavily on a technique known as reinforcement learning that rewards a system for correct answers and punishes it for those that are incorrect. (…)

Mehdi Osman, CEO of software company OpenReplay, said his company traditionally used services from OpenAI, Anthropic and Mistral, and that DeepSeek’s reasoning skills seemed on par with OpenAI’s. “If OpenAI doesn’t reduce their prices, I think many developers will jump to DeepSeek in the coming months,” Osman said. (…)

Much of the spending by the largest cloud-computing companies is going towards Nvidia graphics processing units. Amazon, Google and Microsoft are also building custom chips designed for AI, work that could be less useful in the long term if developers are able to build and run models on less-specialized hardware, Stefan Slowinski, an analyst with BNP Paribas Exane, wrote in a research note on Monday.

DeepSeek’s app proved popular with US users, thanks in part to an affable, somewhat awkward-sounding chatbot that shows in great detail how it plans to respond to a person’s question before diving into the results. The approach includes far more detail than, say, OpenAI’s latest reasoning models. And unlike OpenAI, which charges as much as $200 a month for unlimited access to its most advanced reasoning models, among other features, DeepSeek is currently offering its service for free. But DeepSeek also censors topics that would be sensitive in China. Asking about the Chinese Cultural Revolution, for instance, may provoke the response: “Sorry, that’s beyond my current scope. Let’s talk about something else.” (…) (Bloomberg)

But censoring only happens at data centers. The DeepSeek model open version is not censored when run locally, which most Chinese companies do.

Via John Authers:

As Keith Lerner, chief market strategist at Truist argues, if DeepSeek’s claims are true — that it offers a robust AI tool utilizing low-level Nvidia chips, open-source code, and can be deployed at a fraction of the cost — then it could inspire hundreds of copycats, especially in the US. That’s where the damage will be felt (…).

Also, as experts unravel DeepSeek’s capabilities, they will also get to examine the lofty tech valuations and concentration risks that have grown since ChatGPT’s introduction. An efficient and cost-effective open-source artificial intelligence model should be good news for the economy, but not necessarily for the stock market. (…)

Data centers that support the supercomputers currently thought necessary to run complex AI models also stand to lose.

(…) if DeepSeek’s claims are proven, an aggregate reduction in demand for the chips would damage high expectations for both unit sales and prices (…).

No doubt that AI-related costs, prices and margins will be coming down across the eco-system. Will AI uses (compute) explode as a result (the Jevons Paradox)? How much locally vs via data centers?

• Pat Gelsinger (former Intel CEO) wrote on Linkedin: “The market reaction is wrong: lowering the cost of AI will expand the market. DeepSeek is an incredible piece of engineering that will usher in greater adoption of AI.”
• “DeepSeek is an excellent AI advancement and a perfect example of Test Time Scaling,” Nvidia said, referring to AI systems that consume more computing resources after a user poses a question or sets a task by “reasoning” or taking multiple linked steps to respond. “Inference requires significant numbers of Nvidia GPUs and high-performance networking.” (FT)

That said:

The sky hasn’t fallen just yet. And parallels with the dot-com bubble aren’t quite right. As John Canavan, lead analyst at Oxford Economics, points out, the dot-coms were built on froth. The question was whether they could ever make a profit, and most didn’t. This time, the leading companies are making huge profits, and the question is whether they can be sustained. If they can’t, that will hurt shares in the tech sector, but not necessarily the broader financial markets, or the economy.

Even China’s Property Stalwart Isn’t Immune From the Crisis Troubles at one of China’s largest developers raise questions about the continued spread of the real-estate crisis

China Vanke warned on Monday of a loss of 45 billion yuan, equivalent to around $6.2 billion, for 2024, and said Chairman Yu Liang and Chief Executive Officer Zhu Jiusheng will resign. (…)

Analysts and investors have long seen Vanke as a barometer of how much pain the Chinese government can tolerate amid the country’s epic real-estate bust. The company had been regarded as among the more conservative real-estate companies, eschewing the sort of risky investments that laid low the likes of Evergrande.

Investors will watch to see whether and how the government helps Vanke, as it would indicate the willingness of Chinese authorities to help other struggling state-backed developers to draw a line under the national property crisis.

While many of Vanke’s privately owned peers have suffered liquidity crises and defaulted on their debts in recent years, Vanke has so far managed to stay afloat by making last-minute bond payments and securing fresh loans from banks. By September last year, Vanke’s total liabilities amounted to $136 billion, according to its most recent quarterly report.

In late 2023, when Vanke’s liquidity crunch first emerged, Shenzhen city officials and representatives of Shenzhen Metro voiced their “substantive support” for the company, easing investors’ concern that the company was on the verge of default.

Last April, Vanke said the government of Shenzhen, one of China’s wealthiest cities, was coordinating with state-owned companies to support the developer, including collaborating with it on projects and helping Vanke dispose of properties and equity investments. (…)

Vanke’s sales plummeted 35% in 2024 compared with 2023, to around $51.3 billion, the company said in January. The decline is steeper than that of China’s overall housing sector, where home sales tumbled 18% in 2024, after a 6% decline in 2023. Fitch and S&P Global Ratings downgraded Vanke last week by two notches to B-, citing persistently weak sales and looming debt maturities.

In a separate Hong Kong stock exchange filing, Vanke said the record losses were due to the declining profit margin of real-estate development projects, disappointing sales in 2024 and impairment provision. (…)

Despite efforts by the Chinese government to stimulate the property market, Vanke’s sales in the second half of the year remained sluggish. Its net loss widened from $1.4 billion for the first six months of the year to $6.2 billion for the full year.