to your HTML Add class="sortable" to any table you'd like to make sortable Click on the headers to sort Thanks to many, many people for contributions and suggestions. Licenced as X11: http://www.kryogenix.org/code/browser/licence.html This basically means: do what you want with it. */ var stIsIE = /*@cc_on!@*/false; sorttable = { init: function() { // quit if this function has already been called if (arguments.callee.done) return; // flag this function so we don't do the same thing twice arguments.callee.done = true; // kill the timer if (_timer) clearInterval(_timer); if (!document.createElement || !document.getElementsByTagName) return; sorttable.DATE_RE = /^(\d\d?)[\/\.-](\d\d?)[\/\.-]((\d\d)?\d\d)$/; forEach(document.getElementsByTagName('table'), function(table) { if (table.className.search(/\bsortable\b/) != -1) { sorttable.makeSortable(table); } }); }, makeSortable: function(table) { if (table.getElementsByTagName('thead').length == 0) { // table doesn't have a tHead. Since it should have, create one and // put the first table row in it. the = document.createElement('thead'); the.appendChild(table.rows[0]); table.insertBefore(the,table.firstChild); } // Safari doesn't support table.tHead, sigh if (table.tHead == null) table.tHead = table.getElementsByTagName('thead')[0]; if (table.tHead.rows.length != 1) return; // can't cope with two header rows // Sorttable v1 put rows with a class of "sortbottom" at the bottom (as // "total" rows, for example). This is B&R, since what you're supposed // to do is put them in a tfoot. So, if there are sortbottom rows, // for backwards compatibility, move them to tfoot (creating it if needed). sortbottomrows = []; for (var i=0; i
Is investing in the stock market just like gambling in a casino?
Sometimes it can seem like it because investors and gamblers increasingly use a lot of the same language. That's on purpose, especially on the part of the operators of prediction markets that have only gained regulatory approval to operate in the United States in recent years. The prediction market operators wanted their product to be regulated as a financial product and not as a gambling concern that could limit their growth.
In a preprint version of a paper that will be published in the American Business Law Journal next year, authors Nizan Geslevich Packin, Maya O. Shaton, Elior Sulem, and Sharon Rabinovitz used Large Language Model tools to analyze public records that capture how prediction market operators presented their business to federal regulators to gain their approval.
Here's an excerpt from the paper that explains why the prediction market operators used language to influence regulators and describes how their word choices supported their efforts:
Participants in notice-and-comment processes do not speak randomly. They select terminology and frames they believe will resonate with regulators. In markets characterized by legal ambiguity, this framing becomes especially salient. Describing an activity as “hedging,” “price discovery,” or “risk management” situates it within financial regulation. Describing the same activity as “betting,” “wagering,” or “gaming” situates it within gambling law. Framing therefore operates not only as persuasion directed at agencies, but as a mechanism for shaping the administrative record that courts later treat as the factual predicate for review.
Here's the authors' main findings describing the framing of the words used by the prediction market operators to gain regulatory approval for their businesses as financial institutions, taken from the paper's abstract:
The analysis reveals a pronounced asymmetry: of 812 submissions, 87.2% addressed economic, financial, or regulatory consequences rather than gambling-related characteristics, employing terminology central to financial discourse. Only 5.8% emphasized gambling risks or entertainment dynamics, with high-confidence gambling terminology, with the remaining 7% mixed or neutral.
The initial success of prediction market operators in getting regulated under U.S. financial regulations rather than state gambling laws raises a different question. What makes investing different from gambling?
Schwab's Jonathan M. Craig tackled that question, noting their similarities before identifying the thing that really makes them different:
What investing and gambling have in common is that they both involve risk, and both have potential for gain or loss. But they are not the same—gambling is a game of chance, typically involving short-term bets on binary outcomes. Investing, in contrast, is often a longer-term strategy based on research and data aligned with risk tolerance and financial goals with the aim of acquiring a diversified set of assets that have the potential to appreciate in value and ultimately build wealth for the investor over time.
And to be clear, they have very different expected returns. Studies published by the CFA Institute showed that:
- Over time, gambling always has a negative expected return. In casinos, the built-in mathematical “house edge” reliably leads to a transfer of money from players to the casino. In the long run, the house always wins.
- Investing, on the other hand, is the allocation of capital to a business or asset with the expectation that it will generate income or appreciate in value. Over the past century, investments in stocks and bonds have reliably yielded positive returns. However, keep in mind that the past performance of any investment is not a guarantee of future returns or profits. In the long run, it is possible for both investors and the issuers of securities to earn a positive return.
So where do prediction markets really fall on the investing or gambling spectrum? Should they be regulated like brokerages or as gambling operations?
These questions have been taken on by several courts in cases involving the prediction market Kalshi after it began offering "sports event contracts". The courts have been finding Kalshi has crossed a regulatory line that pushed it into the gambling category, where it must be subject to state level gambling regulations:
The 2nd Circuit denied requests Tuesday (Nov. 3) from Kalshi and Coinbase to block state enforcement while their appeals proceed. The order covered Kalshi’s cases against New York and Connecticut officials and Coinbase’s separate Connecticut case. In the two-sentence order, the panel said the companies had “failed to make the required showing” to justify an injunction pending appeal.
A day later, the 9th Circuit declined to rehear its August decision allowing Nevada to enforce its gambling laws against Kalshi’s sports contracts. The August panel concluded that the sports contracts fell outside the federal definition of swaps, leaving Nevada’s gambling rules applicable. According to the court, no judge called for a vote on rehearing by the full court.
In September, the 6th Circuit cleared the way for Ohio and Tennessee to enforce their laws. It concluded that Kalshi had failed to show its sports contracts qualified as swaps and that, even if they did, federal law would allow the states to enforce their gambling laws.
The Commodity Futures Trading Commission said the Commodity Exchange Act gives it exclusive authority over swaps traded on federally registered exchanges. The dispute turns on whether contracts that pay out based on a game’s outcome fall within the federal definition of a swap and whether the statute displaces state gambling laws as applied to those contracts.
Here's a different question. Does that increasing risk to being regulated as a gambling operation by states make prediction markets a good investment?
That's still an open question, but we do have one interesting data point for it. Online gambling platform DraftKings opened its own prediction market in December 2025. In November 2026, the company reported the high costs of building up its prediction market features is cutting into the company's profits, which in turn, is negatively impacting stock price (NASDAQ: DKNG).
Here are two exit questions. Is that short term pain that will lead to a long-run gain for DKNG investors? And if long-run outcomes is what separates gambling from investing, what amount of time has to pass before the long-run gets here?
Packin, Nizan Geslevich and Shaton, Maya O and Sulem, Elior and Rabinovitz, Sharon, Finance or Gambling? Prediction Markets After Loper Bright and the Administrative Record (February 28, 2026). American Business Law Journal (forthcoming: 2027), Volume 64 Issue 1., Available at SSRN: https://ssrn.com/abstract=6900983 or http://dx.doi.org/10.2139/ssrn.6900983.
Image Credit: Microsoft Copilot Designer. Prompt: "An editorial cartoon of a bull and bear who are trying to decide if they are in a casino or a stock exchange".
Labels: ideas
For the first time since President Donald Trump announced his "Liberation Day" global tariff scheme on 2 April 2025, the combined value of goods exported from the U.S. to China and imported by the U.S. from China has exceeded its pre-tariff war level.
According to international trade data tracked by the U.S. Census Bureau, the total value of goods exchanged between the U.S. and China in September 2026 was $41.1 billion. That surpasses the nominal $40.8 billion figure recorded back in March 2025. It is important to recognize these are nominal data figures, with no adjustment for either inflation in the value of the specific goods being traded between the U.S. and China or seasonality in the data.
The following chart shows September 2026's combined trade value figure, which is 14.7% higher than what was recorded a year earlier, along with the trailing twelve month average for the combined US-China trade figures, which helps address the seasonality in the monthly data. The chart also presents a counterfactual projection for what trade between the U.S. and China would reasonably have looked like based on its pre-global tariff war trend.
Getting deeper into the import and export data, September 2026's trade data breaks down as follows:
Here's is the import and export value data from March 2025 (before the Liberation Day tariffs were announced):
The United States' trade deficit with China has increased since the Liberation Day tariff announcement. That's partly attributable to the difference in each nation's relative economic performance. China has experienced sluggish economic growth, characterized by weak domestic demand, which also lessens the economy's demand for imports. Economic growth in the U.S. during this period has been stronger, driven by the AI technology boom. That boom is responsible for much of the U.S.' increased imports from China, as U.S. domestic production of advanced information technology products is not able to support the increased demand by the economy's information technology sector.
At the same time, we estimate the combined value of trade between the U.S. and China is about 37% less than it would otherwise have been without the global tariff war between the U.S. and China. That estimate is based on the difference between the no-tariff war counterfactual and the trailing twelve month average of the value of goods exchanged between the U.S. and China.
What can we say? International trade is complicated.
U.S. Census Bureau. U.S. International Trade in Goods and Services (FT900). U.S. Trade in Goods with China, Not Seasonally Adjusted, Nominal Figures, Total Census Basis. [Online database]. Accessed 5 November 2026.
Image Credit: Currency collection featuring United States and Chinese banknotes. Photo by Eric Prouzet on Unsplash.
Labels: trade
Younger and older teens saw a split in their job fortunes in October 2026.
Americans Age 16 and 17 saw their seasonally adjusted numbers among the employed increase for the third consecutive month, with 2,028,000 counted as having jobs. It was the first time since March 2026 that the number of working teens reach 2 million or higher as the employment situation younger teens finally appears to be improving after a prolonged downtrend.
Younger teens have seen a better than quarter-million seasonally adjusted increase in their ranks of the employed since bottoming in July 2026.
By contrast, older teens, Age 18 and 19, saw their employment ranks decrease by 90,000 from September 2026's level. Some 3,466,000 members of the older teen demographic were employed in October 2026. Unlike younger teen however, older teens have been seeing their numbers see-saw between 3.4 and 3.6 million since June 2026 as their employment levels have been relatively stable.
The following pair of charts shows the monthly seasonally adjusted data for the working teen demographic from January 2020 through October 2026.
Image Credit: Work Projects Administration Poster Collection, Public domain, via Wikimedia Commons. Original source: National Youth Administration of Illinois. "Get the Facts about Occupations - Free Classes for Young Men and Women 16 to 25 years". This image is in the public domain and is available from the United States Library of Congress's Prints and Photographs division under the digital ID cph.3f05219. We cropped the image for this article.
Labels: demographics, jobs
The S&P 500 (Index: SPX) was heading for a good week. The stock market appeared to react well to news of the Democratic party's sweeps of many elections across the U.S. on Wednesday, 3 November 2026. The index was up almost 1.6% on that news, which seemed contrary to what might be expected for the biggest companies in the index, the Big-AI tech giants, because many of the winning candidates opposed building the data centers they need to support the boom in Artificial Intelligence technologies.
Then Thursday, 5 November 2026 came and the crash that seemed like it should have happened on Wednesday arrived like a ton of weights. It was as if investors suddenly realized that yes, the political party that specifically ran against AI technology development had won power at the federal, state, and local levels of government and would follow through on imposing new regulations and other costs on the AI tech giants. The S&P 500 plunged almost 4.6%, led by AI chipmakers like Nvidia (NASDAQ: NVDA), Micron Technology (NASDAQ: MU), and Advanced Micro Devices (NASDAQ: AMD.
Then Friday arrived and the investors who like to pick through the carrion of market carnage to find deals on heavily discounted stocks found enough among the AI tech sector to boost the index by a little over 0.3% on the day. For the trading week as a whole, the S&P 500 closed the week at 7,376.86, down almost 2.7%.
So what happened on Wednesday to delay the expected drop in stock prices by a day?
The answer turns out to be pretty technical, and to give credit where it's due, Zerohedge provided some of the better reporting of what happened on the day it happened, compiling observations from several sell-side analysts for why the market bounced up instead of realizing the expected drop:
- Clarity - the event is passed and Trump "absolutely willing" to accept the results and a 'medium bad' outcome for Republicans
- Gridlock - lowers the risk premium. Dem majority plus Trump’s willingness to work with it “should act as a break on extreme policy outcomes and bring down risk premia” - DB Saravelos.
- Plunging Oil - recognition of Iran War as reason for Dem Sweep, Trump confirmed he wouldn't escalate in Iran any time soon, and "expect Dems to use fiscal deadlines to seek to limit the war with Iran" - GS Hatzius
- Hopes of Tariff Rollback - "...roll back selected tariffs, and reverse spending cuts enacted last year." - GS Hatzius, and it fits who led today with AAPL/MSFT surging as investors perceived the stock as a winner from the Democratic sweep.
- Hedges Unwound - deeply in the money protection was sold (driving down vol and sparking the heavy delta/gamma flow-driven rebound)
- Technicals - NDX bounced off its 200DMA
- Rotation - Money is moving out of AI CapEx (on worries that Democrats will regulate AI more) and into cash-generating MegaCaps.
- Seasonality - 6 months after the past 19 midterm elections, SPX higher 100% of the time, with an average gain of 14.18%.
We are sure there are more (obviously aside from the classic 'relief rally' argument), but those all seemed to add up to what we saw today...
It was enough to last for a day. And then the Thursday, 5 November 2026 AI Crash happened, where we're now wondering if stock prices are themselves experiencing a regime change. That possibility is hinted at in the latest update, where we find the trajectory of the S&P 500 has dropped well below the range we would expect to find it when investors are focused on the current quarter of 2026-Q4 in setting current day stock prices.
It's too early to tell using the dividend futures-based model since we have to identify potential changes in market regime from observations. On one hand, we have a Lévy flight event where the trajectory of the index has broken away from all of the alternative trajectories it would be expected to be found in the established market regime that's been in place since 28 April 2025. On the other hand, we see that trajectory is on par with where the model would put it in early December 2026, assuming investors are still focusing on 2026-Q4.
The difference between the model's projections in November 2026 and December 2026 could be attributed to how its projections work. Here, its projections a month into the future are "locked in", while its projections of the more distant future are still dynamic and can adapt and provide accurate predictions assuming the existing market regime still holds.
We'll find out which scenario applies in the weeks ahead as investors absorb the random onset of new information from the newstreams. Like those they absorbed from the market moving headlines of the week that was.
The CME Group's FedWatch Tool sees just two more increases in the Federal Funds Rate in the weeks ahead. It continues to anticipate the Fed's next rate hike will be a quarter point, coming on 9 December (2026-Q4). The other rate hike the FedWatch tool foresees would be another quarter point increase that would take place on 17 March (2027-Q1).
The Atlanta Fed's GDPNow tool projects the current quarter of 2026-Q4's inflation-adjusted economic growth rate will be +3.4%, up from its initial estimate of 3.2% a week earlier.
Image credit: Microsoft Copilot Designer. Prompt: "An editorial cartoon of a Wall Street bear who has set a balloon labeled 'AI' on the ground and is trying to crush it with several large weights that say 'REGIME CHANGE' and 'NEW REGULATIONS' and 'HIGHER COSTS' and 'LOWER PROFITS'".
A crime has been committed. The cops think they know who did it, but they don't have enough evidence to make the case. Unless they can get the suspect to confess, they're not going to. They've tried almost all the tricks of their trade to get them to admit they did it, but have come up empty. They're down to their last trick.
It's time to turn to the supernatural. They put the suspect in a darkened room and make them wait, alone. After enough time has passed, a panel in the wall quietly opens, revealing a skeleton with glowing red eyes. Blue lights flash and a voice emanates from the surreal inquisitor. It demands the suspect confess. And the suspect, scared out of their wits, does. The police have their confession, which they've filmed and recorded for use in a court of law. Case closed.
Or at least, that's how Helene Adelaide Shelby imagined how a confession might be obtained when she filed a patent for her invention of an Apparatus for Obtaining Criminal Confessions on 16 August 1927. Here's an excerpt from U.S. Patent 1,749,090, which she was finally awarded on 4 March 1930:
The present invention relates to a new and useful apparatus for obtaining confessions from culprits, or those suspected of the commission of crimes, and photographically recording these confessions, in the form of sound waves, in conjunction with their pictures, depicting their every expression and emotion, to be preserved for later reproduction as evidence against them.
The primary object of my invention is the provision of an apparatus for the creation of illusory effects calculated to impress the subject with their being of a supernatural character and to so work upon his imagination as to enable an inquisitor operating in conjunction with-the recording system to obtain confessions and graphically record them by light action under the control of electric impulses governed by varying intensities of sound waves....
My apparatus for obtaining confessions of guilt from criminals undergoing examination comprises a novel combination of well known elements, arranged in such manner and combination as to produce, when operated, a state of mind calculated to cause him, if guilty, to make confession thereof, the apparatus further operating to record photographically his every expression and emotion, while, at the same time, simultaneously recording his examiners questions and the replies thereto.
The illustrations from her patent reveal the secrets of the supernatural character she envisioned, "a figure in the form of a skeleton", with eyes lit by red lightbulbs to emit "an unnatural ghastly glow":
There's a movie camera rigged up to peer through the nose of a skeleton that's been propped up and cinematically lit behind the sliding panel to the suspect interrogation room to be as spooky as possible. A megaphone transmits the police interrogator's voice while a microphone records the verbal communication, fully synchronized with the film of the suspect and permanently recorded to be projected with sound on a screen later.
That recording system may be the most remarkable aspect of the patent. When Helene Adelaide Shelby filed the patent in August 1927, it was the era of silent films. It wasn't until October 1927 that The Jazz Singer would be released to movie theaters to become the first "full-length" movie production to feature fully synchronized dialogue spoken by its actors on screen. It used the Vitaphone system, which played a wax disc recording of the movie's sound in sync with the film's scenes.
Shelby's invention, on the other hand, appears to utilize a system similar to the Movietone sound system, a sound-on-film technology that was just starting to be used in Hollywood at the time the patent was filed.
Alas, we couldn't find any record of any police department utilizing Shelby's invention. Nor could we find any record of such a system being used to obtain a criminal confession. Not even in the movies.
Labels: technology
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