Money Stuff: The Warner Deal Will Take a While

It’s perhaps worth saying that Paramount Skydance Corp.’s tender offer for Warner Bros. Discovery Inc. is not exactly a classic hostile tender offer. Warner has signed a merger agreement with Netflix Inc., in which Netflix would buy most of Warner for about $27.75 per share in cash and stock, leaving Warner’s shareholders with a bit of the company worth somewhere between $1 and $5 per share. That merger will take a long time to complete. For one thing, Warner’s shareholders have to vote on it, which means that Netflix and Warner need to put together a proxy statement and prospectus for the deal, file it with the US Securities and Exchange Commission and hold a shareholder vote; that could take months. For another, bigger thing, the US Department of Justice will need to review the deal for antitrust concerns; those concerns are significant, and Netflix and Warner have budgeted at least a year for that review.

That deal was announced last Friday, and on Monday Paramount jumped in with an all-cash $30-per-share offer to buy all of Warner, which we discussed on Monday. It took the offer directly to Warner’s shareholders: It launched a tender offer, scheduled to expire on Jan. 8, to buy those shares. The two deals operate on different timelines: Warner plans to ask its shareholders to vote on the Netflix deal, but that vote will happen long after Jan. 8, and if Paramount buys all the shares before the vote then the question is moot. If the shareholders all sell their shares to Paramount in January, they can’t vote on the Netflix deal in March. (And if 51% of the shareholders sell to Paramount, Paramount will control Warner, vote down the Netflix deal and acquire the company itself.)

That is the classic benefit of the hostile tender offer: It’s fast. If Paramount’s tender is more appealing than Netflix’s merger, then Warner shareholders will sell their shares to Paramount before the Netflix vote, and Paramount will win. And if the deals are roughly equally appealing — if shareholders are more or less indifferent between the two bids — then the speed of the tender offer is a real advantage. Shareholders think “ehh, I don’t care much, but if I tender to Paramount I’ll get this done faster, so I might as well tender,” and Paramount wins.

Or that is the classic theory, but it is hard to achieve in practice, and it’s not really true here. Paramount’s offer says at the top that it expires on Jan. 8, but it’s not like it will buy the shares on Jan. 9. Even if 51%, or for that matter 100%, of Warner’s shareholders tender into Paramount’s offer, the offer will not close until two other conditions are met [1] :

1. Paramount’s deal also requires antitrust clearance; it is not legally allowed to buy the Warner shares until it gets that clearance. For a combination of fundamental and Trumpy reasons, Paramount thinks that it will have a much easier time getting antitrust clearance than Netflix would. But it still takes time. “Paramount’s proposal expects to receive regulatory approvals (likely within 12 months),” says Paramount’s presentation: faster than Netflix’s expected timeline, but a lot slower than Jan. 8. 
2. Paramount’s deal is, by its terms, conditional on becoming a friendly deal: A condition of its offer is that “Warner Bros. shall have entered into a definitive merger agreement with Paramount and the Purchaser substantially in the form of the merger agreement submitted by Paramount to Warner Bros. on December 4, 2025.” [2] That is, Paramount does not just want to buy a majority of Warner’s stock and block the Netflix deal that way; it wants Warner’s board to abandon the Netflix deal, pay the $2.8 billion reverse termination fee, and sign a deal with Paramount instead. The deal is too big, and the antitrust approvals and financing are too complicated, to do as a purely hostile deal. Paramount will need Warner’s help to close its deal.

In some sense, then, the Paramount deal is not a “real” tender offer, one that depends only on the shareholders, one that the shareholders can accept even over the board’s objections. The Paramount deal is a pressure tactic, a way to get shareholders thinking “hey I would rather get $30 in a year than $27.75 in 18 months” and telling the board that. If the shareholders all would tender into the Paramount deal, then it’s hard for the board to stick with the Netflix deal, as a matter of fiduciary duties and shareholder pressure. But it’s not like, if the shareholders all do tender into the Paramount deal, it will just close. It’s a jumping-off point for negotiations.

And so Bloomberg’s Lucas Shaw reports that Paramount and Neftlix “are girding for a battle they predict will stretch well into 2026”:

Warner Bros. was given 10 business days to respond to Paramount’s hostile $30-a-share bid for the company on Monday. Since that offer was already rejected once, the Warner Bros. board isn’t planning to cancel the merger agreement signed last week with Netflix, according to people familiar with the company’s thinking. Doing so would require Warner Bros. to pay Netflix a $2.8 billion termination fee.

That puts the onus on Paramount to make the next move in what everyone expects to be a drawn-out affair lasting months. Paramount can follow through on its tender offer to buy Warner Bros. shares from investors at $30 each on Jan. 8. It can also extend the bid, sue to stop the Netflix deal or increase the terms. …

Shareholders of Warner Bros., one of Hollywood’s biggest film and TV companies, are hoping for a bidding war that further boosts the price of the deal. … Both companies have communicated that they have the ability to increase their offers, according to the people, who asked not to be identified discussing private deliberations.

And the Financial Times notes:

Some WBD shareholders expect Paramount to lift its bid before the tender offer expires, after Ellison’s company said in a regulatory filing that $30 was not its “best and final” price.

Paramount is privately weighing an increase, or whether to instead add sweeteners intended to give WBD’s board greater confidence in its regulatory prospects versus Netflix, according to people familiar with the matter. 

Yeah you don’t go around saying on television, as Paramount did, that your offer is “not best and final” if you want shareholders to tender so you can close next month. They know there’s a lot of negotiation to come.

Historically you needed investment banks to figure out the price of securities for you. If you wanted to buy a bond, you would call up a trader at a bank and say “what is the price of this bond,” and she would tell you. How would she know? Well, she would spend all day buying and selling that bond and other bonds like it. She just sold a bunch of them to a big asset manager, and bought some more from a hedge fund, and she knows the prices they paid, and she can extrapolate from there. Her answer will not be simple and mechanical; she will have a thought process like “I sold some of these bonds before lunch at $100, but that was to a really big client so I quoted them a good price, and since then Treasuries have traded 5 basis points wider and an analyst released a bearish report on this company’s equity,” and she’ll adjust the price to reflect current circumstances. Her prices will be informed by her experience of financial markets and her particular knowledge of the stuff she trades.

Similarly, if a company wanted to issue some new bonds of its own, it would call up a banker and say “what rate will we have to pay on our bonds,” and the banker would tell it. How would he know? These bonds don’t trade — they don’t exist yet — so there is no market price. But he spends all day doing bond deals like this. He knows what companies are comparable to this company, and where their bonds trade, and what sort of concessions investors would demand for a new bond from this company. 

If you wanted to buy a share of stock, you might also call a trader at a bank and say “what is the price of this stock,” but in recent decades that process has been almost totally automated. The stock trades continuously in a liquid public market; you can just read the price of the stock off the order book. Someone is setting the prices on the order book — some trader, historically often at a bank, bids to buy the stock at $49.99 and offers to sell it at $50.01 or whatever — but it’s probably a computer. You could figure out the price of a stock using deep connoisseurship, long expertise of financial markets and particular knowledge of the individual stock. But in practice, for small stock trades, what you want is speed and efficiency, and it mostly turns out that you can make markets in stocks using quite simple heuristics. “Move your market up a penny when you buy, move it down a penny when you sell, and adjust for any moves in S&P 500 futures” is probably reasonably close to the algorithm that many sophisticated high-frequency trading firms use, these days, to price stocks. Deep connoisseurship is useful in making concentrated long-term investing decisions, but the classic work of market making can be done pretty simply by algorithms.

That has been largely true about stocks for decades, but for a long time it was not so true about bonds. There were too many bonds, each was unique, they had complicated terms, etc. etc. etc., so they were traded by humans. In recent years that distinction has been collapsing. It is more complicated for a computer to trade bonds than it is to trade stocks; the algorithm needs to have a bit more connoisseurship; it needs to pull in more data and do more complicated interpolations to figure out the right price. But the algorithms got better, and now they often do have sufficient connoisseurship to trade bonds.

Do they have sufficient connoisseurship to underwrite bonds? Could a company call up an algorithm and say “what rate will we have to pay on our bonds” and get a good answer? Why not? We talked seven years ago about a financial technology startup whose “main offering is a set of machine-learning algorithms powered by neural networks, a type of artificial intelligence, that predict the timing and pricing of new bond issues.” Apparently it has since shut down, so maybe not the best proof of concept. But I used to be a convertible bond underwriter, so I would get those calls from companies asking what rate they would pay on their (convertible) bonds, and I know the process that I used to answer the question. The process consisted mostly of looking at a big Excel file where we kept track of all of the convertible bond deals and sort of eyeballing where the company might land. My connoisseurship was not that deep. A computer could probably manage.

The extreme case, for an investment bank, is mergers and acquisitions. If a company wants to sell itself, it calls up a mergers and acquisitions banker and says “what price will we get if someone acquires us,” and the banker tells it. How does she know? Well, she spends all day doing deals like this. She knows what companies are comparable to this company, and where their stocks trade. She knows what deals have happened in the sector, and at what prices. She knows this company’s business, and its financial prospects, and can build a discounted cash flow model to value the company; she has a sense of what assumptions are reasonable to plug into that model. She knows who the potential buyers are; she has long-term relationships with the other strategic buyers in the sector and with the financial sponsors who might be interested. She can put together a plan to market the company and persuade buyers to pay a high price.

There is a ton of connoisseurship and expertise and particular knowledge and nuance here. She’s not going to just spit out a price, and you’re not necessarily going to get whatever price she comes up with: Her price is only an estimate, and a jumping-off point for marketing and negotiations; the actual price will depend on months of deal dynamics. Also coming up with the price is only a small part of her job; most of her job is getting that price, finding the buyers and getting them to the table and negotiating with them. Still. If you called an M&A banker and said “we’re thinking of selling our company, what price do you think we’d get” and she said “man I have no idea, depends on what people want to pay,” you might lose confidence in her. The number she comes up with is maybe not that meaningful on its own, but it is in some sense a shorthand for her knowledge of your company and the market, and her aggressiveness in getting a deal done.

Can a computer do that? Oh I mean sure eventually, why not. The M&A banker has, in her head and also probably in a spreadsheet, some set of comparable precedent deals, and she uses them to interpolate a price for the next deal. Seems pretty computerizable. But you do have to get the deals into the algorithm. Bloomberg’s Todd Gillespie reports:

Investment banks are pulling together data from years of deals they’ve arranged in order to get an edge on competitors in an sector increasingly dependent on artificial intelligence.

Boutique investment banks including Moelis & Co. and Houlihan Lokey Inc. are building out datasets of deal history to support their investment bankers. Some are also making money by selling data to clients, executives said Tuesday at the Goldman Sachs Financial Services Conference.

“We have a project going on working out how to integrate a lot of this data we’ve collected over the last 18 years and making sure that our data is usable and can plug into these AI tools,” said Moelis Chief Executive Officer Navid Mahmoodzadegan, whose firm was founded in 2007. “How do we use that data to win business, give better advice and make transactions happen?” …

At Houlihan Lokey, known for broking a high volume of mid-market deals, executives say they have an edge because of the size of its dataset.

“Having statistically significant datasets really allows us to analyze things differently and on a basis really where we can have an information set that others don’t,” said CEO Scott Adelson.

Houlihan Lokey — which hired a BlackRock Inc. executive last year to build out the firm’s data efforts — used data from its portfolio-valuation business to launch a private credit data platform, which aggregates data from more than 60,000 loan valuations and is accessible to some clients.

The algorithms that you use to price 100-share stock trades are informed by decades of second-by-second public trading data. The algorithms that you use to track middle-market M&A or loan deals should be informed by years of deals that were privately negotiated by fax and telephone and email, memorialized in Microsoft Word contracts and then maybe (or maybe not) entered into an Excel file by a junior analyst who left years ago. If you can plug all that stuff into the AI, the AI can help do the deals.

Private markets, I often say around here, are the new public markets. These days, a company can become a household name, have a celebrity chief executive officer, be a constant fixture on financial television, raise tens of billions of dollars from institutional investors, offer liquidity to employees and early investors, have a stock price that is frequently updated based on market activity, attract meme-ish retail investors, and generally do almost everything that a large public company could do, without being public.

This is arguably nice for the company — no activist investors or short sellers to deal with, no need to make public filings, etc. — but people tend to assume that it’s unstable. Eventually a giant private company has to go public to justify and realize its private valuation; eventually, the only way for early investors and employees to fully cash out is with a publicly traded stock. [3]  Companies can delay their initial public offerings longer than they used to — they can stay private longer, and grow bigger, than they used to — but eventually there has to be an IPO.

When they do, though, it will be a new kind of IPO. There have been a few — Facebook and Uber come to mind — that are arguably in roughly the same category, tech startups that went public when they were already huge and household names. But their valuations at IPO were an order of magnitude smaller than the projected IPO valuations of the current crop of companies like OpenAI and SpaceX. Bloomberg’s Edward Ludlow and Eric Johnson report on SpaceX’s IPO plans:

SpaceX is moving ahead with plans for an initial public offering that would seek to raise significantly more than $30 billion, people familiar with the matter said, in a transaction that would make it the biggest listing of all time.

The Elon Musk-led company is targeting a valuation of about $1.5 trillion for the entire company, which would leave SpaceX near the market value that Saudi Aramco established during its record 2019 listing. The oil major raised $29 billion at the time.

SpaceX’s management and advisers are pursuing a listing as soon as mid-to-late 2026, said some of the people, who asked not to be identified because the matter is confidential. The timing of the IPO could change based on the market and other factors, and one of the people said it could slip into 2027. ...

SpaceX expects to use some of the funds raised in an IPO to develop space-based data centers, including purchasing the chips required to run them, two of the people said, an idea Musk expressed interest in during a recent event with Baron Capital.

I guess if you do an IPO in 2026 you might as well position yourself as an AI data center company (in space). 

But what does an IPO of a $1.5 trillion household-name Elon Musk company look like in 2026? Some traditional things you might say about an IPO are:

1. IPO investors are taking a lot of risk on the company’s valuation, so they expect to be rewarded with a big IPO “pop.”
2. Banks need to explain and market the company to new investors, to get them to take that risk.
3. The stock trading shortly after the IPO will be volatile, because the company is new and untested, most of the stock is not available for trading, and the stock is migrating from a private shareholder base to a different public shareholder base.

Does SpaceX look like that? Or are private markets the new public markets, to the extent that SpaceX will just sort of slide seamlessly into the public markets? Its current shareholders include Fidelity and other public-type investors, as well as various vehicles marketing to individual investors. Its stock trades, sort of:

In the current secondary offering, SpaceX has set a per-share price of around $420, putting its valuation above the $800 billion previously reported, people familiar with the discussions said. The company is allowing employees to sell about $2 billion worth of stock, and SpaceX will participate in buying back some shares, two of the people said.

The valuation strategy is designed to level-set the company’s fair market valuation in a precursor to the IPO, one of the people added.

And Bloomberg’s Bailey Lipschultz and Loren Grush note:

“The median market cap of an S&P 500 company is close to $40 billion; this is a completely different stratosphere,” said Paul Abrahimzadeh, a partner at 1789 Capital and a former co-head of equity capital markets for North America at Citigroup Inc. “A company like SpaceX will clearly cater to a wide swath of institutional investors — as well as retail — and is a must-own name.” …

A SpaceX listing as soon as mid-2026 could resolve the disconnect between public and private markets in a flood of mega-deals that some investors can’t afford to miss.

As Rob Stowe, Barclays’ head of Americas ECM, put it: “Large deals have their own gravity.” ...

If an investor sits out an IPO that raises $500 million or less and it does well, that won’t really impact their performance, Stowe said. However, “if you choose not to participate in a $30 or $50 billion IPO that does really well, that creates some significant challenges.”

If you are a public-market investor benchmarked to the stock index, you need a really good reason to avoid owning a massive index constituent like Apple Inc. or Nividia Corp. or Tesla Inc. If SpaceX is a trillion-dollar company, then it is kind of automatically in that category too. Right now, investors have a really good reason not to own it: It’s not public, so they can’t. As soon as it goes public, that excuse goes away.

Stock investors are humans, so stock price returns have some patterns driven by predictable human behaviors. Volumes tend to be low in August, because all the senior traders are on vacation. There is perhaps some evidence for a “lunch effect,” where stocks go up a bit right after lunch because investors are well-fed and happy and ready to buy. You can’t take this stuff too seriously. Financial markets offer large and legible rewards for being on the other side of predictable irrational human behaviors. If you know that fat happy traders will be buying stock at 12:30, you should eat lunch early, buy stock at 12:20, and sell it to them. If you know that you’ll be trading against inexperienced junior traders in August, you should go to the beach in July and fleece the juniors in August. There is money to be made if you can suppress your own human instincts and trade against people who don’t, and that’s pretty much what hedge funds are for.

Still here’s this:

Binge-watching late-night TV shows has become far more common due to the popularity of streaming services such as Netflix and Amazon and their ‘dump release’ of new shows at midnight. We examine how the sleep loss associated with this phenomenon affects financial markets and find that market returns significantly decline on the day following the release of popular late-night shows. This effect is stronger in stocks with larger market-cap, and higher price. We show that sleep-deprived investors are less willing to make buying decisions since they require larger cognitive effort compared to selling decisions. Instead, they make more heuristic-driven sales, causing a decline in market returns.

That is from the abstract to “The Morning After: Late-night TV and the Stock Market,” by Arbab Cheema, Arman Eshraghi, P. Raghavendra Rau and Qingwei Wang. I find this charming but a bit hard to believe, especially this part:

On average, the S&P 500 index drops by about 0.25% on the day following these shows. Annually, the decrease in market returns is around 2.3% cumulatively, based on an average of 10 popular shows being released every year. The effect is more pronounced in stocks with larger market capitalisation, higher institutional ownership, and higher stock price. Perhaps sleep deprivation due to late-night shows should affect individual investors more than professional traders or institutional investors. Sleep hours of such professionals, however, are lower than others (Kamstra et al., 2000; Siganos, 2021). Therefore, their sleep will deteriorate even further if they are watching late-night shows. Thus, the effect is stronger for stocks that are the habitat of institutional investors. The fact that there is a market-wide effect on returns, predominantly in large-cap stocks with high institutional ownership, implies that sleep deprivation affects the behaviour of institutional investors who currently hold most of the U.S. firms’ stocks.

I’m not sure you should take that too seriously either. The theory here is that institutional investors don’t get enough sleep anyway,  so when they binge a season of Stranger Things in one night they are particularly unlikely to buy any stocks the next day. But: Why are they bingeing a season of Stranger Things in one night? Surely they get paid enough to wait until the weekend?

Also I do not think that the right interpretation here is “if streamers stopped dumping whole seasons at midnight, stock market returns would be 2.3% higher each year” — presumably they do their buying the next day? — but it would be funny if it was. The business of allocating capital is hard and time-consuming, and if television is too good then capital allocation will suffer.

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