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
Political Calculations' initial estimate of the total value of new home sales in the United States during July 2026 is $28.41 billion. This value is slightly lower than the initial estimate of $28.62 billion we presented in our previous update that covered new home sales data through May 2026.
Since then, the number of new home sales has been trending downward thanks largely to an increase in mortgage rates in recent months, which has made new homes relatively less affordable during this time. The number of new home sales has dropped to its lowest level since the start of the year.
One surprising development however is that the average new home sale prices has also declined in recent months. Builder incentives are making new homes less expensive than existing homes.
As far back as modern records go, newly built homes have almost always cost more than previously owned homes.
It only makes sense: New homes are expected to have far fewer maintenance issues, brand new appliances, and designs suited to contemporary tastes, plus they can be customized to suit the homebuyer's needs.
After all, it is only in very rare circumstances that a used car would cost more than a similar make and model purchased brand new at the dealer's lot.
But in recent months, that trend has been upended to an extent that has never been seen, with the typical new home selling at a sharp discount to existing homes.
In June, the $407,200 median sales price of new homes was about $28,000 less than for existing homes, a 6.5% discount and by far the biggest inversion in at least 25 years.
Last month, the gap narrowed a bit to nearly $19,000, or 4%—still significantly larger than any discount seen before this year. July also marked the fourth straight month of price inversion for new homes, the longest stretch on record.
The following charts present the U.S. new home market capitalization, the number of new home sales, and their average sale prices as measured by their time-shifted, trailing twelve month averages from January 1976 through July 2026.
We'll update our measure of the relative affordability of new homes sometime in the next week.
U.S. Census Bureau. New Residential Sales Historical Data. Houses Sold. [Excel Spreadsheet]. Accessed 25 August 2026.
U.S. Census Bureau. New Residential Sales Historical Data. Median and Average Sale Price of Houses Sold. [Excel Spreadsheet]. Accessed 25 August 2026.
Image Credit: An aerial view of a lot of houses photo by Modunite Ltd on Unsplash.
Labels: market cap, real estate
We recently discussed how advances in technology are contributing to boosting the productivity of mathematicians during the last thirty years. But the chart we featured in that article depicting how the number of math papers being published each month has nearly doubled in the last three years may not do full justice to how fast the pace of new papers coming out has changed.
Another way to communicate that acceleration in output is Matt Parker's approach of focusing on a small subset of the new papers being published in the last few months to show how they represent a big increase in the capability of the AI large language models used to generate their findings. In the following video, in what is becoming an annual tradition, he interrupts his vacation to cover breaking news in the world of mathematics.
Parker makes an explicit point of noting the use of the Lean proof assistant to verify their findings, which gives greater confidence the findings in these papers will stand up to serious scrutiny.
Not all the preprint papers that have recently populated the mathematics category of the arXiv database meet that standard, as Reddit math community poster Salt_Attorney recently observed.
By contrast, Lean verification was used in the ten advances spanning several disciplines in mathematics OpenAI claims its Astra AI system has made. As such, they have a much better chance they'll be found valid when the findings are reviewed.
But the question now being raised is whether verification of findings by a proof assistant is enough to accept AI-generated results as presented. For further reading on that topic, we'll recommend Gary Marcus' discussion of OpenAI's claimed accomplishment to appreciate it may not be either as grand or the Astra AI system as capable as presented in OpenAI's announcement.
Labels: ideas, math, technology
The S&P 500 (Index: SPX) dropped almost 1.4% from its previous week's close to wrap up the trading week ending on Friday, 21 August 2026 at 7,678.76.
Rising bond yields was perhaps the biggest driver of stock prices during the week, which comes as the U.S. government is increasingly having to compete with Big Tech to borrow money as the company's seeking to build out the infrastructure to support the expansion of Artificial Intelligence (AI) systems are borrowing big to do it.
One outcome of that dynamic is expectations of higher interest rates. The CME Group's FedWatch Tool projections of the expected future for how the Fed will set the Federal Funds Rate changed little in the past week. It anticipates a 60% chance the Fed will act to hike this core interest rate to a target range of 3.75-4.00% on 28 October (2026-Q4), while giving a much stronger 98% chance this rate will be in effect on 9 December (2026-Q4). Beyond that, the FedWatch Tool now anticipates another quarter point rate hike on 28 April (2027-Q2).
Meanwhile, stock prices behaved almost exactly as would be expected if investors were tightly focusing on 2027-Q1 as they set the level of the week's stock prices. The latest update of the alternative futures chart shows that outcome as the S&P 500's trajectory closely paced the dividend futures-based model's projection associated with investors fixing their attention on the distant future quarter of 2027-Q1.
Investors had quite a lot of other new information to absorb during the trading week. Here is the summary of the week's market-moving headlines:
The Atlanta Fed's GDPNow tool anticipates +4.0% real GDP growth for the U.S. economy in 2026-Q3, dipping from the +4.3% annualized growth it projected a week earlier.
Image credit: Microsoft Copilot Designer. Prompt: "An editorial cartoon of a Wall Street bull holding up a sign that says 'RISING BOND YIELDS' who is growling at scared investors"
It may not seem like it, but the millennia-old academic discipline of mathematics has been undergoing a productivity revolution during the last thirty years.
That revolution is being enabled by the adoption of several new technologies, each of which is following a S-shaped logistic growth curve model. Mike Roberts of Strategic Tool Kits describes the pattern of how technological advancements increase performance over time:
The S curve is a strategic concept that describes how the old ways mature and are superseded by new ways.
In the early days of new technology, it takes a long time to improve performance. People are working out the technology, and the applications, ironing out the flaws, and building the ecosystem. Slowly over time, performance accelerates.
After a certain time, the rate of improvement hits a peak and then starts to slow down. Easy wins have all been made and the learning curve has been fully ridden for continuous improvement. Some of the fundamental barriers of the technology are reached. Eventually, the improvement tapers off and a plateau with this technology is reached. This is the “S” shaped curve.
When a new productivity-enhancing technology comes along after the older technology reaches its mature phase, the process repeats with performance building on its old plateau and rising to new heights.
For mathematicians, the two great technological improvements of the twenty-first century have been the widespread adoption of the arXiv database for publishing preprint papers to more quickly communicate their discoveries and the more recent development of Artificial Intelligence (AI) systems paired with proof assistant systems like Lean that are helping automate large portions of their work.
ArXiv provides data on the number of new papers that are uploaded to its preprint paper database each month. The following chart reveals its data for math papers, not counting cross listings from other categories of academic papers, from January 1992 through July 2026:
The data shows adoption of the arXiv database for communicating advancements in maths went through the full S-curve advancement cycle, reaching a fully mature phase by the early 2020s with output holding fairly level for several years. But after ChatGPT (3.5) was launched at the end of November 2022, the Large Language Model (LLM) technology facilitiated a steady increase in the productive output of mathematicians for the first time in years. By making it possible to automate a portion of writing academic papers, the number of papers published to arXiv each month began to rise in a steady, linear trend.
But soon after OpenAI's o3-mini LLM-based reasoning model was released on 31 January 2025, the rate of output for publishing new papers to arXiv exploded in what appears to be the exponential growth phase of the S-shaped logistic growth pattern. The new cost efficient o3-mini reasoning model was specifically developed to automate analytical tasks in Science, Technology, Engineering, and Mathematics fields and also coding.
For mathematics, the new AI technologies make rapid advancements possible by drawing on the body of published work, like the thousands of math preprint papers documented in the arXiv database and other resources that catalogued large numbers of unresolved conjectures in digital-friendly formats, to test new possible ways of testing those conjectures. When promising proofs or disproofs of the conjectures are identified, the technology automates their verification using the proof assistant software technology that has also come into its own during this period. Using proof assistants also has the benefit of coding any new successful proofs into their proof libraries, which can then be mixed and matched as needed to test other conjectures.
When that's done, the remaining step for the mathematicians orchestrating what's effectively become a massive, automated collaboration exercise is to write up a new preprint paper and publish it to the arXiv database.
Mathematics isn't the only field experiencing a boom in preprint papers. Economics has likewise seen the number of papers published each month almost double since ChatGPT 3.5's public release. Unlike math however, economists don't have the equivalent of maths' proof assistants to verify their findings, which raises questions about the quality and validity of the flood of new papers in the field.
arXiv. Math Submissions. [Online Database]. Accessed 8 August 2026.
arXiv. Monthly Submissions. [Online Article and CSV Data]. Accessed 8 August 2026.
Ecology.net. Logistic Growth. [Online Article]. 15 December 2025.
Pablo Groisman. Math papers uploaded to arXiv per month, January 1992 to July 2026. [Online Article]. 3 August 2026. [Our article was inspired by Pablo's chart!]
Mike Roberts. S Curve – What is it? [Online Article]. 13 July 2024.
ScriptByAI. OpenAI & ChatGPT Timeline: GPT Release Dates to GPT-5.6 (2026). [Online Database]. Accessed 20 August 2026.
Image credit: S Curve Concept in Science by Oliver Tacke on Wikiversity. Creative Commons CC BY-SA 3.0 Attribution-ShareAlike 3.0 Unported Deed. 17 July 2012.
When we launched the S&P 500's Thanksgiving Leftover project the day after Thanksgiving 2025, we knew we were going to spend the next year following the stock prices of companies that weren't doing very well. After all, to even make the list, the ten companies whose stocks we would track ranked as the S&P 500's worst performing stocks of 2025.
In the nine months since then, a few of those stocks have outperformed the index, while the rest have lagged behind. Most of those stocks have fallen below their post-2025 Thanksgiving Day level, but not by anywhere near as much as they had fallen to qualify as one of the S&P 500's worst performing stocks in 2025.
But one stock in particular has gone on to plumb new depths. It has continued to fall so much more that it is on track to qualify as one of the S&P 500's worst performing stocks of 2026.
That stock is The Trade Desk (NASDAQ: TTD), the digital advertising firm analyst David Desjardins believes is facing an "existential crisis". Here's how he describes the company's now nearly two year long fall from grace:
After reporting highly disappointing financial results for the second quarter of 2026, shares of The Trade Desk, Inc. (TTD) declined by a whopping 21.9% last Friday, which came on top of a 6.8% decline on the prior day. Since the publication of my initiating coverage in early February 2026, TTD's stock price has basically been cut in half, from ~$27.00 per share at the time of publication to around $13.39 as of today's market close.
Relative to its all-time high of $141.53 reached in December 2024, The Trade Desk has now declined by a massive ~90%. As David Einhorn famously said, a stock down 90% is just a stock that was down 80% before being cut in half again, and this is exactly what happened to TTD since last February. The depth of TTD's sell-off is quite something, but what is even more impressive to me is its speed....
At this point, The Trade Desk has become one of the most hated stocks that I am aware of, and this is on top of being the worst-performing constituent in the S&P 500 (SPX) on a year-to-date basis. Pretty much everything said or written about the company is negative, and it is precisely why I decided to write an update today. In less than two years, TTD went from a market darling that could do no wrong at over 26.0x forward sales to being viewed as a melting ice cube changing hands at 2.3x forward sales today.
The following chart compares The Trade Desk's stock performance with the S&P 500, from 29 November 2024 (aka "the day after Thanksgiving Day 2024) through 18 August 2026:
Believe it or not, despite the company's continued misfortune, Desjardins views the company's low stock price as a speculative strong buy opportunity, where he makes the argument that the company has some potential for a turnaround based on its available cash balance, lack of debt, and cash flow.
We disagree, because we think The Trade Desk has further to fall before it might reach that point.
Here's why. According to SlickCharts, The Trade Desk's market cap has fallen to where the company now ranks 502 out of the 503 stocks that make up the S&P 500 index. Because it has, and because its fall is continuing, the company's stock is verging on the point where S&P will act to remove it from the index. If and when that happens, as increasingly seems likely, its stock price will experience the opposite of what happens when a company's stock is included in the index, which is to say its stock price will fall even further.
A deeper decline is almost ensured given the negative outlook CEO Jeffrey Green communicated during the company's 2026-Q2 earnings call. Gytis Zizys, who formerly held a buy rating for the company on the hope it will see a turnaround, reacted to that development:
The Trade Desk, Inc. (TTD) provided one of the worst guidances I’ve seen in recent months, which put the last nail in the coffin for many shareholders who were still clinging to the idea of a turnaround. It seems I was prematurely too bullish on the turnaround as well, and this report is forcing me to downgrade it to a hold. I don’t think there’s a point in selling at these low prices, unless you want to harvest some tax losses. If it gets to under $10 per share, I will be jumping in to see what happens over the next couple of years. It’ll either recover, or my investment will go to zero.
The only problem with this investing strategy is we can argue that the bar for being able to beat TTD's stock performance is very low. It's so low that investing almost anywhere else or just parking the money in a cash savings account would be more advantageous.
This article is a standalone feature in our ongoing Thanksgiving Leftover series, which will continue with its regular monthly installment later this month. The ongoing tragedy of the performance of The Trade Desk's stock demanded a special edition.
Labels: ideas, SP 500, stock prices, thanksgiving
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Closing values for previous trading day.
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