WSJ : As Trump Readies a Reset of Antitrust Policy, Look to These Sectors for De

As Trump Readies a Reset of Antitrust Policy, Look to These Sectors for Deals
Change in leadership of the Federal Trade Commission could spark M&A in tech, healthcare and beyond

Donald Trump’s victory could prove to be just what the doctor ordered for dealmakers. That is particularly the case in sectors where consolidation has been most held back, including tech and healthcare. But much remains to be seen—especially considering some of the populist forces that helped propel the 45th President to another term.

Wall Street’s dealmakers are already sharpening their pencils. Investment banking titans Goldman Sachs, Morgan Stanley and JPMorgan Chase saw their stocks notch their biggest single-day gains in four years the day after the election. Megacap tech companies have also rallied—adding $773 billion to their collective market cap this week—while biotech stocks have jumped. One big reason for the optimism is the belief that the incoming administration will prove much more friendly to major mergers and acquisition transactions that have been increasingly off the table for these industries over the past four years.

Few figures in the Biden administration have clashed more with American corporations than Lina Khan, the 35-year-old chair of the Federal Trade Commission. Khan has been a vocal opponent of tech giants, challenging companies like Microsoft MSFT -0.68%decrease; red down pointing triangle, Google, Amazon AMZN -0.89%decrease; red down pointing triangle and Meta Platforms META -0.40%decrease; red down pointing triangle. The exit of Khan and her Justice Department counterpart, Jonathan Kanter, would signal a shift to a more relaxed antitrust stance.

While antitrust policy isn’t the only factor influencing M&A, loosening restrictions could unleash pent-up demand. The market could use the boost. Last year saw the lowest number of M&A deals targeting U.S. companies since 2015, and this year is on pace to close with an even smaller number of transactions announced, according to data from Dealogic.

Megadeals have faced a particularly high barrier—especially those by companies that regulators in the U.S. and Europe have deemed “Too Big to Deal.” Enhanced scrutiny has significantly increased the time required to close deals of this scale. It took Microsoft nearly two years to complete its $75 billion acquisition of Activision Blizzard that wrapped last year, compared with the six months required to close its next largest deal—the takeover of LinkedIn in 2016.

Such lengthy waits act as another barrier to dealmaking. Amazon gave up on buying roomba-maker iRobot IRBT 0.80%increase; green up pointing triangle earlier this year after 17 months; it took the e-commerce giant less than three months to clear its acquisition of Whole Foods in 2017—at nearly eight times the price. Adobe ADBE -1.25%decrease; red down pointing triangle likewise walked away from an effort to buy design software maker Figma late last year after 15 months. By contrast, the average time to close major U.S. tech deals from 2018 through 2020 was a little under six months, according to Dealogic.

In healthcare, a shift in antitrust policy could enable pharmaceutical companies to pursue larger biotech acquisitions or even consider megamergers between pharma giants of the kind that were once common in the industry. In recent years, smaller deals of $5 billion or less have become much more popular in healthcare, while big or even midsize acquisitions have become less frequent. Notable exceptions were Pfizer’s PFE -1.18%decrease; red down pointing triangle $43 billion buyout of Seagen and Amgen’s $27.8 billion acquisition of Horizon Therapeutics, though the FTC tried to stop the latter and might have looked more favorably on the former due to Pfizer’s positive role during the pandemic. Megadeals like Bristol Myers’ BMY -1.04%decrease; red down pointing triangle acquisition of Celgene for $74 billion in 2019 or Pfizer’s $68 billion acquisition of rival Wyeth in 2009 have been out of the question.

Health insurers might also see new opportunities. For instance, some on Wall Street expect that talks for a Humana HUM 0.13%increase; green up pointing triangle-Cigna blockbuster deal—which The Wall Street Journal reported took place last year—could be revived. Humana stock is up over 10% since Trump’s victory, also due partly to expectations of a more favorable Medicare Advantage policy.

In recent years, many in Silicon Valley and in the biotechnology industry have voiced concerns that the Biden administration’s tough antitrust stance was eroding investor confidence in their ability to realize returns on investments. Critics argue that for venture capitalists to continue funding new ventures, they need the assurance that they can eventually reward shareholders through exits, often in the form of mergers or acquisitions.

Khan and her defenders argued that they weren’t out to stop all deals, simply the ones that led to a higher concentration of market power that would eventually harm consumers. That created a bias among industry titans against large deals that could be susceptible to regulatory attention.

“Obviously, anyone who wants to speculate about these things would have to immediately consider the global regulatory environment,” Disney DIS 0.09%increase; green up pointing triangle Chief Executive Bob Iger said on an earnings call last year, when asked about the oft-circulated rumor that Apple AAPL -0.12%decrease; red down pointing triangle might seek to buy the entertainment giant.

One important cautionary note: There is no guarantee that Trump will totally dial back antitrust scrutiny. Vice President-elect JD Vance is among a group of populist Republicans who have taken a more skeptical view of corporate power. Some have referred to them as Khanservatives, a nod to Lina Khan’s populism. Another: There is no assurance that key regulators abroad, who have to approve many large-scale mergers that affect their markets, would follow a Trump administration’s lead, especially if trade relations get more contentious.

Dealmaking depends on much more than just antitrust policy. Interest rates and the availability—and valuation—of suitable targets matter just as much. But dealmakers over the past four years have also had to factor in the growing odds that the federal government will just say no. Now they at least have a chance to reset those odds.

FT : US oil industry eagerly awaits Donald Trump’s deregulatory push

US oil industry eagerly awaits Donald Trump’s deregulatory push
Despite president-elect’s promises, production is unlikely to surge as Wall Street demands returns over growth

US oil executives are eagerly awaiting Donald Trump’s expected rollback of environmental regulations, but despite the president’s pledge to “drill, baby, drill”, production is unlikely to increase significantly during his second term in office. 

Trump made energy policy a pillar of his campaign, vowing to slash red tape and unshackle US oil producers to drive up production and bring down prices for consumers.

“We have more liquid gold than any country in the world — more than Saudi Arabia,” Trump said as he claimed victory early on Wednesday morning. 

The former president’s re-election is a boon for the industry, which had a tumultuous relationship with Joe Biden’s administration. It is also a big pay-off for the corporate leaders who poured money into his campaign war chest. 

“I couldn’t be more thrilled by president-elect Donald Trump’s victory,” said Continental Resources founder Harold Hamm, a Trump donor. “This is a monumental win for American energy and the future of our nation’s security.”

Jeff Miller, chief executive of Halliburton, one of the country’s biggest oilfield service companies, echoed those sentiments. “It could only be positive. In fact, I’m quite optimistic,” he said. 

On taking office next January, the industry expects Trump to slash many of the environmental rules imposed by Biden. Mike Sommers, head of the American Petroleum Institute, said there had been a “regulatory onslaught” during the past four years that would now be reversed. 

“Just the signal from the administration that they want a robust oil and gas industry in the US is going to be a major component to getting this industry the investment that it needs to continue to grow,” he said. 

Among the changes the industry expects are the abolition of rules on tailpipe emissions designed to push motorists towards electric vehicles, as well as expanded access to hydrocarbons through increased leasing in the Gulf of Mexico and on public lands, and the dilution of protections for endangered species. Trump is also predicted to end a pause on new licences for liquefied natural gas terminals.

Trump has vowed to slash corporate tax and unpick Biden’s signature climate legislation, the Inflation Reduction Act. But many in the industry benefit from the IRA and are lobbying against its wholesale removal.

Trump has already begun to shape the team that will be responsible for making these changes. North Dakota governor Doug Burgum is in contention for a new “energy tsar” role that will co-ordinate the deregulatory drive across a patchwork of government agencies.

But despite the anticipated regulatory overhaul, analysts warned that a rapid increase in output during Trump’s second term was unlikely. Production has hit record levels during Biden’s term in office, reaching a fresh high of 13.4mn barrels a day in August despite the regulations. 

But investors — burnt after years of debt fuelled drilling binges — are keen for companies to prioritise returns over growth. The model of capital discipline they have imposed on the sector is unlikely to change. 


“Price and Wall Street are the regulators of US production, not the president,” said Jim Burkhard, head of research for oil markets at consultancy S&P Global. 

Production is set to average about 13.2mn barrels a day this year, according to S&P, rising to 13.6mn b/d in 2025 before probably slipping the following year, driven by lower prices. Trump’s re-election does not change its near term outlook.

Macroeconomic factors, however, may help Trump keep his promise to bring down prices at the pump: sluggish Chinese demand coupled with Opec+ plans to increase supplies are likely to depress prices in the months ahead. But that would have a negative impact on oil producers.

“The market is oversupplied because the Chinese economy is not delivering the kind of demand that it has in the past,” said Daniel Yergin, a Pulitzer Prize-winning energy historian and author of The New Map. “That is the biggest overhang for the global and US oil industry.”

Bob McNally, president of consultancy Rapidan Energy and a former energy adviser to the George W Bush administration, said that while “any president has very limited tools to impact the price of oil in the short term” if strong global supply growth outpaces demand in the coming years, Trump “may get lucky and witness a sharp decline in oil prices”.

“However, he would relearn a lesson from 2020, which is that low oil prices may please consumers, but they also hurt the US shale oil sector,” he said. “In fact the biggest threat to the US shale sector is sharply lower oil prices.”

Trump showed during his first term he was willing to play an active role in shaping the oil price. In 2018, he browbeat Opec into increasing production to bring down prices at the pump, before convincing them to slash it in 2020 to save the US shale patch from bankruptcy as prices plunged in the wake of the coronavirus pandemic. 

Trump has also vowed to exert maximum pressure on Iran, ramping up sanctions on its oil exports, which could push up the global oil price.

One of the most fundamental changes sought by the industry is for Trump, aided by Republican control of the Senate and potentially the House of Representatives, to push through far reaching permitting reform legislation after years of failed attempts. 

Alan Armstrong, head of pipeline giant Williams said he was “very hopeful with more Republican control that the permitting issue finally gets dealt with in a durable and meaningful way”.

Despite Trump’s plans to tear up environmental rules, analysts expect large public oil companies to remain motivated to curb emissions — especially when it comes to methane, a potent greenhouse gas.

“I think the expectation that they will be reducing emissions and investing in clean energy does not go away because Donald Trump was elected,” said Paul Bledsoe, a former climate adviser to the Bill Clinton administration.

“I think that’s a public expectation. That’s an investor expectation.”

FT : How Thames Water became a battleground for hedge funds

How Thames Water became a battleground for hedge funds
Rival groups of bondholders are vying to extend loans to the troubled UK utility

In spring this year, Elliott Management, the $70bn US hedge fund known for circling distressed assets, alighted on a new target: Britain’s largest water company.

After scooping up hundreds of millions of pounds of Thames Water’s debt from panicked asset managers willing to sell at a discount, Paul Singer’s Elliott is now one of several hedge funds engaged in a tussle over the future of the troubled utility.  

Elliott, which earned notoriety for seizing a Argentine naval ship during a 15-year skirmish with the Latin American nation over its defaulted debt, is in the vanguard of a group of Thames Water’s top-ranking bondholders that has agreed to provide a loan of as much as £3bn to the cash-strapped utility, which has warned that without urgent intervention it could run out of money around Christmas.

The emergency loan will not come cheap. On top of a near 10 per cent annual interest rate, the lenders will also pocket substantial fees and stand to gain a further windfall if Thames Water repays the loan ahead of its 2.5-year maturity.

While Thames Water has already signed a so-called lock-up agreement with these bondholders and is trying to gain approval for the deal from the rest of its lenders, a rival group of investors holding the utility’s lower-ranking debt has made a competing offer to provide their own £3bn loan at a lower 8 per cent interest rate and with fewer strings attached.

The two sets of bondholders include large asset managers such as BlackRock — which is in both groups through investments in separately managed funds — but the competing offers have also pitched a number of specialist distressed debt investors against one another. Elliott is joined by fellow US hedge funds Silver Point Capital and GoldenTree Asset Management in the so-called class A bonds and the likes of London-based credit fund Polus Capital Management hold the class B debt.

The fact that the utility, which provides water and sewerage services to 16mn customers in and around London, is now host to a fight between some of the US and Europe’s biggest debt specialists underscores its fall from grace in debt markets.

Thames Water’s near £19bn of debt was once viewed as among the safest investments in the sterling corporate bond market, due to the regulated regional monopoly’s predictable revenue stream. But now credit rating agencies have downgraded the utility to the lowest reaches of junk.

While both proposed loans have been pitched as short-term solutions to keep Thames Water afloat while it tries to raise at least another £3bn in fresh equity from new investors, some campaigners fear it could saddle the company with even more expensive debt to the detriment of its customers.

Feargal Sharkey, the former rock musician who now campaigns for cleaner water in Britain and is fiercely critical of industry regulator Ofwat, said that “customers would pay for this as more of their bills get eaten by savage lenders”.

“Ofwat seems content to allow Thames Water’s debilitated corpse to implode under even yet more debt,” he said, “while the vulture capitalists and banks look on, licking their lips, eager for a quick buck.”

A spokesperson for the class A bondholders said that their loan offer “is open to all creditors” and that they want to “give Thames the best opportunity to attract the new equity it needs and allow for a full recapitalisation and successful turnaround”.

A spokesperson for the class B bondholders said that their financing offer was “drastically cheaper, more flexible and more substantial than the expensive loan proposed by the class A [group]”.

Ofwat said: “’We have been pushing Thames Water to make significant improvements in its operational performance and financial resilience for some time.”

“The company has made a request for a substantial increase in expenditure as part of the current price review process. We are reviewing that request and the supporting information provided, and will announce our final decisions in December.”

People close to the class A bondholders argue that their overall deal will lessen the company’s immediate debt repayment burden, due to a maturity extension that Thames Water would simultaneously gain from lenders, while freeing up hundreds of millions of pounds of cash currently trapped in reserve accounts.

The interest on the new debt would be funded from the proceeds of the loan itself rather than customer bills, those people also claimed.

But it is also true that there is the potential for instant profits to the funds that participate: traders have already started quoting conditional prices on the new debt showing that they will buy and sell it well above face value.

The class B bondholders, meanwhile, have said that Thames Water has not given a fair hearing to their offer, which they estimate could save the utility hundreds of millions of pounds.

“They said ‘it’s all too little too late’,” one bondholder said. 

Credit funds such as Sculptor Capital Management and Marathon Asset Management are among the funds that have provided commitments to fund the class B group’s loan, according to people familiar with the matter.

Sculptor declined to comment. Marathon did not respond to a request seeking comment.

Zimmer Partners — a US investment firm that specialises in utilities and infrastructure — is one of the biggest funders of the rival loan offer, the people added. The New York-based firm has experience in providing rescue financing to troubled utilities, having provided $675mn of equity to bankrupt Californian electricity company PG&E in 2020.

PG&E’s bankruptcy also prompted a tussle between hedge funds that saw Elliott and Zimmer sit in opposing camps, with the former firm unsuccessfully pursuing legal action against the company for allegedly snubbing Elliott from participating in a $2bn equity raise.

Elliott and Zimmer also declined to comment.

While there are heavyweight firms on both sides, the class B bondholders are relative minnows in Thames Water’s debt stack, accounting for £1.4bn of its borrowing versus £16bn of class A debt. The class A bondholders would be paid ahead of any class B if the utility were to become insolvent, while the new loan would rank ahead of both classes of existing debt.


Even though the class B bondholders are offering cheaper terms, their proposed loan would still need approval from class A bondholders. This could prove a sticking point.

The class B group said on Thursday that it was calling on “all of the company’s other creditors to support this committed financing [ . . .] rather than needlessly paying lenders interest on expensive debt with money that could be spent investing in the water and wastewater supplies of London and the Thames Valley”.

If either loan goes through, it will allow Thames Water to keep running while Ofwat agrees a five-year regulatory settlement over customer bills, which is expected to be announced in December or early January.

It will also give the utility breathing room to potentially challenge the regulator with the Competition and Markets Authority if the settlement disappoints. The company has asked for a 53 per cent increase in bills by 2030.

“If they raise £3bn debt, this should get you to the other side of any CMA referral, so the can may be well and truly kicked down the road,” said Dominic Nash, an analyst at Barclays.

The equity process is being run separately by Rothschild with final bids due early in the new year. Potential bidders including Castle Water, which already handles Thames Water’s business customers, and US private equity firm KKR are carrying out due diligence on the deal, according to two people familiar with the situation.

Some have argued that an onerous new loan or a messy dispute between bondholders could make Thames Water less appealing to potential investors, however.

“If that exploitative deal is agreed we will definitely consider walking away,” said one potential equity investor.

The bondholders declined to comment. Thames Water did not respond to a request seeking comment.

But while the two groups of bondholders are at odds over which loan deal goes through, they are unified in their determination to avoid the renationalisation of Thames Water under the government’s special administration regime.

With any new funding from the government ranking ahead of their debt in that process, special administration would have the potential for inflicting large losses even on hedge funds that scooped up Thames Water’s debt for pennies on the pound.

>>> Fed's Kashkari (non-voter for 2024 and 2025): If growth and productivity rem

Fed's Kashkari (non-voter for 2024 and 2025): If growth and productivity remain strong the Fed may not cut as much - Fox News interview
- Reiterates that housing inflation will take a while to come down all the way
- Have made progress but want to get the job done on inflation
- Not concerned about the dynamic in Washington between the Fed and the incoming Trump Admin
- Deficit and debt levels are up to Congress and the President
- All things being equal, if tax cuts are paid for they are less likely to cause inflation

The Information : OpenAI Shifts Strategy as Rate of ‘GPT’ AI Improvements Slows

OpenAI Shifts Strategy as Rate of ‘GPT’ AI Improvements Slows

The Takeaway
• The increase in quality of OpenAI’s next flagship model was less than the quality jump between the last two flagship models
• The industry is shifting its effort to improving models after their initial training
• OpenAI has created a foundations team to figure out how to deal with the dearth of training data

The number of people using ChatGPT and other artificial intelligence products is soaring. The rate of improvement for the basic building blocks underpinning them appears to be slowing down, though.

The situation has prompted OpenAI, which makes ChatGPT, to cook up new techniques for boosting those building blocks, known as large language models, to make up for the slowdown.

The challenges OpenAI is experiencing with its upcoming flagship model, code-named Orion, show what the company is up against. In May, OpenAI CEO Sam Altman told staff he expected Orion, which the startup’s researchers were training, would likely be significantly better than the last flagship model, released a year earlier.

Though OpenAI had only completed 20% of the training process for Orion, it was already on par with GPT-4 in terms of intelligence and abilities to fulfill tasks and answer questions, Altman said, according to a person who heard the comment.

While Orion’s performance ended up exceeding that of prior models, the increase in quality was far smaller compared with the jump between GPT-3 and GPT-4, the last two flagship models the company released, according to some OpenAI employees who have used or tested Orion.

Some researchers at the company believe Orion isn’t reliably better than its predecessor in handling certain tasks, according to the employees. Orion performs better at language tasks but may not outperform previous models at tasks such as coding, according to an OpenAI employee. That could be a problem, as Orion may be more expensive for OpenAI to run in its data centers compared to other models it has recently released, one of those people said.

The Orion situation could test a core assumption of the AI field, known as scaling laws: that LLMs would continue to improve at the same pace as long as they had more data to learn from and additional computing power to facilitate that training process.

In response to the recent challenge to training-based scaling laws posed by slowing GPT improvements, the industry appears to be shifting its effort to improving models after their initial training, potentially yielding a different type of scaling law.

Some CEOs, including Meta Platforms’ Mark Zuckerberg, have said that in a worst-case scenario, there would still be a lot of room to build consumer and enterprise products on top of the current technology even if it doesn’t improve.

At OpenAI, for instance, the company is busy baking more code-writing capabilities into its models to head off a major threat from rival Anthropic. And it’s developing software that can take over a person’s computer to complete white-collar tasks involving web browser activity or applications by performing clicks, cursor movements, text typing and other actions humans perform as they work with different apps.

Those products, part of a movement toward AI agents that handle multistep tasks, could prove just as revolutionary as the initial launch of ChatGPT.

Furthermore, Zuckerberg, Altman and CEOs of other AI developers also publicly say they haven’t hit the limits of traditional scaling laws yet.

That’s likely why companies including OpenAI are still developing expensive, multibillion-dollar data centers to eke out as many performance gains from pretrained models as they can.

However, OpenAI researcher Noam Brown said at the TEDAI conference last month that more-advanced models could become financially unfeasible to develop.

“After all, are we really going to train models that cost hundreds of billions of dollars or trillions of dollars?” Brown said. “At some point, the scaling paradigm breaks down.”

OpenAI has yet to finish the lengthy process of testing the safety of Orion before its public release. When OpenAI releases Orion by early next year, it may diverge from its traditional “GPT” naming convention for flagship models, further underscoring the changing nature of LLM improvements, employees said. (An OpenAI spokesperson did not comment on the record.)

Hitting a Data Wall

One reason for the GPT slowdown is a dwindling supply of high-quality text and other data that LLMs can process during pretraining to make sense of the world and the relationships between different concepts so they can solve problems such as drafting blog posts or solving coding bugs, OpenAI employees and researchers said.

In the past few years, LLMs used publicly available text and other data from websites, books and other sources for the pretraining process, but developers of the models have largely squeezed as much out of that type of data as they can, these people said.

In response, OpenAI has created a foundations team, led by Nick Ryder, who previously ran pretraining, to figure out how to deal with the dearth of training data and how long the scaling law will continue to apply, they said.

Orion was trained in part on AI-generated data, produced by other OpenAI models, including GPT-4 and recently released reasoning models, according to an OpenAI employee. However, such synthetic data, as it is known, is leading to a new problem in which Orion may end up resembling those older models in certain aspects, the employee said.

OpenAI researchers are utilizing other tools to improve LLMs during the post-training process by improving how they handle specific tasks. The researchers do so by asking the models to learn from a large sample of problems—such as math or coding problems—that have been solved correctly, in a process known as reinforcement learning.

They also ask human evaluators to test the pretrained models on specific coding or problem-solving tasks and rate the answers, which helps the researchers tweak the models to improve their answers to certain types of requests, such as writing or coding. That process, called reinforcement learning with human feedback, has aided older AI models as well.

To handle these evaluations, OpenAI and other AI developers typically rely on startups such as Scale AI and Turing to manage thousands of contractors.

In OpenAI’s case, researchers have also developed a type of reasoning model, named o1, that takes more time to “think” about data the LLM trained on before spitting out an answer, a concept known as test-time compute.

That means the quality of o1’s responses can continue to improve when the model is provided with additional computing resources while it’s answering user questions, even without making changes to the underlying model. And if OpenAI can keep improving the quality of the underlying model, even at a slower rate, it can result in a much better reasoning result, said one person who has knowledge of the process.

“This opens up a completely new dimension for scaling,” Brown said during the TEDAI conference. Researchers can improve model responses by going from “spending a penny per query to 10 cents per query,” he said.

Altman, too, has emphasized the importance of OpenAI’s reasoning models, which can be combined with LLMs.

“I hope reasoning will unlock a lot of the things that we’ve been waiting years to do—the ability for models like this to, for example, contribute to new science, help write a lot more very difficult code,” Altman said in October at an event for app developers.

In a recent interview with Y Combinator CEO Garry Tan, Altman said, “We basically know what to go do” to achieve artificial general intelligence—technology that is on par with human abilities—and part of it involves “using current models in creative ways.”

Mathematicians and other scientists have said o1 has been beneficial to their work by acting as a companion that can provide feedback or ideas. But the model is currently priced six times higher than nonreasoning models, and as a result it doesn’t have a broad base of customers, said two employees with knowledge of the situation.

‘Breaking Through the Asymptote’

Some investors who have poured tens of millions of dollars into AI developers have wondered whether the rate of improvement of LLMs is beginning to plateau.

Ben Horowitz, whose venture capital firm is both an OpenAI shareholder and a direct investor in rivals such as Mistral and Safe Superintelligence, said in a YouTube video that “we’re increasing [the number of graphics processing units used to train AI] at the same rate, but we’re not getting the intelligent improvements at all out of it.” (He didn’t elaborate.)

Horowitz’s colleague, Marc Andreessen, said in the same video that there were “lots of smart people working on breaking through the asymptote, figuring out how to get to higher levels of reasoning capability.”

It’s possible that the performance of LLMs has plateaued in certain ways but not others, said Ion Stoica, a co-founder and chair of enterprise software firm Databricks and a co-developer of a website that allows app developers to evaluate different LLMs.

While AI has continued to improve in tasks like coding and solving complex, multistep problems, progress appears to have slowed in AI models’ ability to carry out general-purpose tasks like analyzing the sentiment of a tract of text or describing the symptoms of a medical issue, Stoica said.

“For general-knowledge questions, you could argue that for now we are seeing a plateau in the performance of LLMs. We need [more] factual data, and synthetic data does not help as much,” he said.