Here is a personal economical anecdote from this week. A medium-sized dead branch fell from a tall tree and ripped off the driver side mirror on my old Honda. My local repair shop said it would cost around $600 to replace it. That is a significant percentage of what the old clunker is worth. Ouch.
They kindly noted that most of that cost would was ordering a replacement mirror assembly from Honda, which would cost over $400 and take several days to arrive. I asked if I could try to get a mirror from a junkyard, to save money. The repair guy said they would be willing to install a part I brought in, but suggested eBay or Amazon instead.
Back 20 years ago, before online commerce was so established, my local repair shop would routinely save us money by getting used parts from some sort of junkyard network. So, I started looking into that route. First, junkyards are not junkyards anymore, they are “salvage yards.” Second, it turns out that to remove a side mirror from a Honda is not a simple matter. You have to remove the inside whole plastic door panel to get at the mirror mounting screws, and removing that panel has some complications. Also, I could not find a clear online resource for locating parts at regional salvage yards. It looks like you have to drive to a salvage yard, and perhaps have them search some sort of database to find a comparable vehicle somewhere that might have the part you want.
All this seemed like a lot of hassle, so I went to eBay, and found a promising looking new replacement part there for about $56, including shipping. It would take about a week to get here (probably being direct shipped from China). On Amazon, I found essentially the same part for about $63, that would get here the next day. For the small difference and price, I went the Amazon route, partly for the no hassle returns if the part turned out to be defective and partly because I get 5% back on my Amazon credit card there. I just got the car back from the repair shop with the replacement mirror, and it works fine. The total cost, with labor was about $230, which is much better than the original $600+ estimate.
I’m not sure how broadly to generalize this experience. Some further observations:
( 1 ) For a really critical car part, I’d have to consider carefully if the Chinese knock-off would perform appreciably worse than some name-brand part – -although, I believe many repair shops often use parts that are not strictly original parts.
( 2 ) Commonly replaced parts like oil and air filters are typically cheaper to buy on-line than from your local Auto Zone or other local merchant. I like supporting local shops, so sometimes I eat the few extra $$ and shopping time, and buy from bricks and mortar.
( 3 ) Some repair shops make significant money on their markup on parts, and so they might not be happy about you bringing in your own parts. They also might decline to warrant the operation of that part. And many big box franchise repair shops may simply refuse to install customer-supplied parts.
( 4 ) For a newish car, still under warranty, the manufacturer warranty might be affected by using non-original parts.
( 5 ) Back to junk/salvage yards: there are some car parts, so-called hard parts, that are expected to last the life of the car. Things like the mounting brackets for engine parts. Typically, no spares of these are manufactured. So, if one of those parts gets dinged up in an accident, your only option may be used parts taken from a junker.
Traditional Large Language Model (LLM) artificial intelligence programs like ChatGPT train on massive amounts of human-generated text to be able to mimic human outputs when given prompts. A recent trend (mainly starting in 2024) has been the incorporation of more formal reasoning capabilities into these models. The enhanced models are termed Large Reasoning Models (LRMs). Now some leading LLMs like Open AI’s GPT, Claude, and the Chinese DeepSeek exist both in regular LLM form and also as LRM versions.
The authors applied both the regular (LLM) and “thinking” LRM versions of Claude 3.7 Sonnet and DeepSeek to a number of mathematical type puzzles. Open AI’s o-series were used to a lesser extent. An advantage of these puzzles is that researchers can, while keeping the basic form of the puzzle, dial in more or less complexity.
They found, among other things, that the LRMs did well up to a certain point, then suffered “complete collapse” as complexity was increased. Also, at low complexities, LLMs actually outperform LRMs. And (perhaps the most vivid evidence of lack of actual understanding on the part of these programs), when they were explicitly offered an efficient direct solution algorithm in the prompt, the programs did not take advantage of it, but instead just kept grinding away in their usual fashion.
As might be expected, AI skeptics were all over the blogosphere, saying, I told you so, LLMs are just massive exercises in pattern matching, and cannot extrapolate outside of their training set. This has massive implications for what we can expect in the near or intermediate future. Among other things, the optimism about AI progress is largely what is fueling the stock market, and also capital investment in this area: Companies like Meta and Google are spending ginormous sums trying to develop artificial “general” intelligence, paying for ginormous amounts of compute power, with those dollars flowing to firms like Microsoft and Amazon building out data centers and buying chips from Nvidia. If the AGI emperor has no clothes, all this spending might come to a screeching crashing halt.
Ars Technica published a fairly balanced account of the controversy, concluding that, “Even elaborate pattern-matching machines can be useful in performing labor-saving tasks for the people that use them… especially for coding and brainstorming and writing.”
Comments on this article included one like:
LLMs do not even know what the task is, all it knows is statistical relationships between words. I feel like I am going insane. An entire industry’s worth of engineers and scientists are desperate to convince themselves a fancy Markov chain trained on all known human texts is actually thinking through problems and not just rolling the dice on what words it can link together.
And
if we equate combinatorial play and pattern matching with genuinely “generative/general” intelligence, then we’re missing a key fact here. What’s missing from all the LLM hubris and enthusiasm is a reflexive consciousness of the limits of language, of the aspects of experience that exceed its reach and are also, paradoxically, the source of its actual innovations. [This is profound, he means that mere words, even billions of them, cannot capture some key aspects of human experience]
However, the AI bulls have mounted various come-backs to the Apple paper. The most effective I know of so far was published by Alex Lawsen, a researcher at LLM firm Open Philanthropy. Lawsen’s rebuttal, titled “The Illusion of the Illusion of Thinking, was summarized by Marcus Mendes. To summarize the summary, Lawsen claimed that the models did not in general “collapse” in some crazy way. Rather, the models in many cases recognized that they would not be able to solve the puzzles given the constraints input by the Apple researchers. Therefore, they (rather intelligently) did not try to waste compute power by grinding away to a necessarily incomplete solution, but just stopped. Lawsen further showed that the ways Apple ran the LRM models did not allow them to perform as well as they could. When he made a modest, reasonable change in the operation of the LRMs,
Models like Claude, Gemini, and OpenAI’s o3 had no trouble producing algorithmically correct solutions for 15-disk Hanoi problems, far beyond the complexity where Apple reported zero success.
Lawsen’s conclusion: When you remove artificial output constraints, LRMs seem perfectly capable of reasoning about high-complexity tasks. At least in terms of algorithm generation.
And so, the great debate over the prospects of artificial general intelligence will continue.
According to Merriam-Webster, “money” is: “something generally accepted as a medium of exchange, a measure of value, or a means of payment.” Money, in its various forms, also serves as a store of value. Gold has maintained the store of value function all though the past centuries, including our own times; as an investment, gold has done well in the past couple of decades. I plan to write more later on the investment aspect, but here I focus on the use of physical gold as a means of payment or exchange, or as backing a means of exchange.
Gold, typically in the form of standardized coins, served means of exchange function for thousands of years. Starting in the Renaissance, however, banks started issuing paper certificates which were exchangeable for gold. For daily transactions, the public found it more convenient to handle these bank notes than the gold pieces themselves, and so these notes were used instead of gold as money.
In the late nineteenth and early twentieth centuries, leading paper currencies like the British pound and the U.S. dollar were theoretically backed by gold; one could turn in a dollar and convert it to the precious metal. Most countries dropped the convertibility to gold during the Great Depression of the 1930’s, so their currencies became entirely “fiat” money, not tied to any physical commodity. For the U.S. dollar, there was limited convertibility to gold after World War II as part of the Bretton Woods system of international currencies, but even that convertibility ended in 1971. In fact, it was illegal for U.S. citizens to own much in the way of physical gold from FDR’s (infamous?) executive order in 1933 until Gerald Ford’s repeal of that order in 1977.
So gold has been essentially extinct as active money for nearly a hundred years. The elite technocrats who manage national financial affairs have been only too happy to dance on its grave. Keynes famously denounced the gold standard as a “barbarous relic”, standing in the way of purposeful management of national money matters.
However, gold seems to be making something of a comeback, on several fronts. Most notably, several U.S. states have promoted the use of gold in transactions. Deep-red Utah has led the way. In 2011, Utah passed the Legal Tender Act, recognizing gold and silver coins issued by the federal government as legal tender within the state. This legislation allows individuals to transact in gold and silver coins without paying state capital gains tax. The Utah House and Senate passed bills in 2025 to authorize the state treasurer to establish a precious metals-backed electronic payment platform, which would enable state vendors to opt for payments in physical gold and silver. The Utah governor vetoed this bill, though, claiming it was “operationally impractical.”
The new legislation, House Bill 1056, aims to give Texans the ability, likely through a mobile app or debit card system, to use gold and silver they hold in the state’s bullion depository to purchase groceries or other standard items.
The bill would also recognize gold and silver as legal tender in Texas, with the caveat that the state’s recognition must also align with currency laws laid out in the U.S. Constitution.
“In short, this bill makes gold and silver functional money in Texas,” Rep. Mark Dorazio (R-San Antonio), the main driving force behind the effort, said during one 2024 presentation. “It has to be functional, it has to be practical and it has to be usable.”
Arkansas and Florida have also passed laws allowing the use of gold and silver as legal tender. A potential problem is that under current IRS law, gold and silver are generally classified as collectibles and subject to potential capital gains taxes when transactions occur. Texas legislator Dorazio has argued that liability would go away if the metals are classified as functional money, although he’s also acknowledged the tax issue “might end up being decided by the courts.”
But as Europeans found back in the day, carrying around actual clinking gold coins for purchasing and making change is much more of a hassle than paper transactions. And so, various convenient payment or exchange methods, backed by physical gold, have recently arisen.
Since it is relatively easy and lucrative to spawn a new cryptocurrency (which is why there are thousands of them), it is not surprising that there are now several coins supposedly backed by bullion. These include include Paxos Gold (PAXG) and Tether Gold (XAUT). The gold of Paxos is stored in the worldwide vaults of Brinks, and is regularly audited by a credible third party. Tether gold supposedly resides somewhere in Switzerland. The firm itself is incorporated in the British Virgin Islands. Tether in general does not conduct regular audits; its official statements dance around that fact. These crypto coins, like bullion itself or various funds like GLD that hold gold, are in practice probably mainly an investment vehicle (store of value), rather than an active medium of exchange.
However, getting down to the consumer level of payment convenience, we now have a gold-backed credit card (Glint) and debit card (VeraCash Mastercard). Both of these hold their gold in Swiss vaults. The funds you place with these companies have gold allocated to them, so these are a (seemingly cost-effective) means to own gold. If you get nervous, you can actually (subject to various rules) redeem your funds for actual shiny yellow metal.
Yesterday I got a scary-sounding text message, claiming that I have an outstanding traffic ticket in a certain state, and threatening me with the following if I did not pay within two days:
We will take the following actions:
1. Report to the DMV Breach Database
2. Suspend your vehicle registration starting June 2
3. Suspension of driving privileges for 30 days…
4. You may be sued and your credit score will suffer
Please pay immediately before execution to avoid license suspension and further legal disputes.
Oh, my!
A link (which I did NOT click on) was provided for “payment”.
I also got an almost (not quite) identical text a few days earlier. I was almost sure these were scams, but it was comforting to confirm that by going to the web and reading that, yes, these sorts of texts are the flavor of the month in remote rip-offs; as a rule, states do not send out threatening texts with payment links in them.
These texts are examples of “smishing”, which is phishing (to collect identity or bank/credit card information) via SMS text messaging. It must be a lucrative practice. According to spam blocker Robokiller, Americans received 19.2 billion spam robo texts in May 2025. That’s nearly 63 spam texts for every person in the U.S.
Beside these traffic ticket scams, I often get texts asking me to click to track delivery of some package, or to prevent the misuse of my credit card, etc. I have been spared text messages from the Nigerian prince who needs my help to claim his rightful inheritance; I did get an email from him some years back.
The FTC keeps a database called Sentinel on fraud complaints made to the FTC and to law enforcement agencies. People reported losing a total of $12 billion to fraud in 2024, an increase of $2 billion over the previous year. That is a LOT of money (and a commentary on how wealthy Americans are, if that much can get skimmed off with little net impact on society). The biggest single category for dollar loss was investment; the number of victims was smaller than for other categories, but the loss per victim ($9,200) was quite high. Other areas with high median losses per capita were Business and Job Opportunities ($2,250) and Mortgage Foreclosure Relief and Debt Management ($1,500).
Imposter scams like the texts I have gotten (sender pretending to be from state DMV, post office, bank, credit card company, etc.) were by far the largest category by number reported (845,806 in 2024). Of those imposter reports, 22% involved actual losses ($800 median loss), totaling a hefty $2,952 million. That is a juicy enough haul to keep those robo frauds coming.
How to not get scammed: Be suspicious of every email or text, especially ones that prey on emotions like fear or greed or curiosity and try to engage you to payments or for prying information out of you. If it purports to come from some known entity like Bank of America or your state DMV, contact said entity directly to check it out. If you don’t click on anything (or reply in any way to the text, like responding with Y or N), it can’t hurt you.
I’m not sure how much they can do, considering the bad guys tend to hijack legit phone numbers for their dirty work, but you can mark these texts as spam to help your phone carrier improve their spam detection algorithm. Also, reporting scam texts to the U.S. Federal Trade Commission and/or the FBI’s Internet Crime Complaint Center can help build their data set, and perhaps lead to law enforcement actions.
Later add: According to EZPass, here is how to report text scams:
You can report smishing messages to your cell carrier by following this FCC guidance. This service is provided by most cell carriers.
Hold down the spam TXT/SMS message with your finger
Select the “Forward” option
Enter 7726 as the recipient and press “Send”
Additionally, to report the message to the FBI, visit the FBI’s Internet Crime Complaint Center (ic3.gov) and select ‘File a Complaint’ to do so. When completing the complaint, include the phone number where the smishing text originated, and the website link listed within the text.
According to the U.S. Department of Agriculture, feral hogs cause approximately $2.5 billion in agricultural damages each year…Nearly 300 native plant and animal species in the U.S. are in rapid decline because of feral swine, and many of the species are already at risk, according to Animal and Plant Health Inspection Service. The swine also carry at least 40 parasites, 30 bacterial and viral illnesses, and can infect humans, livestock and other animals with diseases like brucellosis and tuberculosis.
…They will also feed on tree seeds and seedlings, causing significant damage in forests, groves and plantations… Rooting — digging for foods below the surface of the ground — destabilizes the soil surface, uprooting or weakening native vegetation, damaging lawns and causing erosion. Their wallowing behavior destroys small ponds and stream banks, which may affect water quality. They also prey upon ground-nesting wildlife, including sea turtles. Wild hogs compete for food with other game animals such as deer, turkeys and squirrels, and they may consume the nests and young of many reptiles, ground-nesting birds and mammals.
Pigs are smart (ahead of dogs and horses), tough, and adaptable, and they breed very quickly. The protected, overfed, calm hogs you see on farms quickly turn lean and mean if they have to fend for themselves in the wild. You pretty much only see female pigs or castrated males on the farm, since whole males (boars) are intrinsically aggressive and destructive. But vigorous 200-pound boars, with their 3 inch-long, razor-sharp tusks, are well-represented in feral swine.
This is a growing problem. The population of wild pigs in the southern third of the U.S. has increased significantly in the past few decades. There have historically been some wild pigs in spots like Florida and Texas, escapees from Spanish settlers long ago. But they seem to be spreading northward, largely because hunters transplant them:
From 1982 to 2016, the wild pig population in the United States increased from 2.4 million to an estimated 6.9 million, with 2.6 million estimated to be residing in Texas alone. The population in the United States continues to grow rapidly due to their high reproduction rate, generalist diet, and lack of natural predators. Wild pigs have expanded their range in the United States from 18 States in 1982 to 35 States in 2016. It was recently estimated that the rate of northward range expansion by wild pigs accelerated from approximately 4 miles to 7.8 miles per year from 1982 to 2012 (12). This rapid range expansion can be attributed to an estimated 18-21% annual population growth and an ability to thrive across various environments, however, one of the leading causes is the human-mediated transportation of wild pigs for hunting purposes.
As for pigs attacking and killing humans, a definitive study was recently made in 2023 by Mayer, et al., covering 2000-2019. This report includes informative tables and charts, such as:
and
Comparison of mean annual number of human fatalities from attacks by various wild animals for time periods ranging between 2000 and 2019. From Mayer, et al.
About half of these fatalities occurred in rural regions of India. Government policies there prohibit farmers from killing marauding pigs, so farmers try to chase them away from their fields with rakes and stones. Sometimes that provokes the pig to attack, slashing at thigh level and often lacerating the femoral artery. But a disturbing 39% of deadly attacks were unprovoked, including a horrific case with an elderly woman in Texas. So danger to humans is an issue, though for perspective, far more people are killed each year by snakes (100,000), rabid dogs (30,000), and crocodiles (1000). In the U.S., over 100 people are killed a year, and 30,000 injured, by collisions with deer (see here for a market-based solution for this problem).
What to do? Hunters in many states are free to blast away at feral pigs year-round, since they are considered a harmful, invasive (non-native) species. Paradoxically, however, allowing hunting of pigs can be counterproductive: amateur hunting does not eliminate enough pigs to stop their spread, and it incentivizes hunters to transport pigs to new regions to make for more targets. For instance, Arkansas allows hunting and even transport of pigs, and has seen swine populations skyrocket. The state of Missouri, next door, took the enlightened approach of banning hunting and transport, leaving population control to wildlife professionals. By removing the sport-hunting incentive, Missouri removed the incentive to transport them, which stymied their spread.
To control pig populations, the pros mainly set up baited large corrals, and monitor them remotely with webcams. After several weeks, the local pigs get comfortable coming there to feed. When the cameras show that every single pig in the herd is in the corral, the gate is sprung shut remotely. Then the pros drive out to, er, euthanize the pigs. The goal is to wipe out the entire herd, and leave no sadder-but-wiser survivors who will be harder to catch next time. Once a hog population has become established in an area, it typically takes ongoing eradication efforts to keep the numbers down.
If you want to do your own part to reduce the surplus swine population, the following notable opportunity came to my attention: for a largish fee the Helibacon company will train you in firing automatic weapons and take you up in a chopper where you can mow down a marauding herd in the low Texas scrubland. It sounds like a guy thing, but Helibacon reminds us that full auto is for ladies, too. See also PorkChoppersAviation for similar service.
This is actually a fine example of a free market solution to a problem: wild hogs were such a problem for landowners that they were paying expensive professional helo hunters to take out herds, but in Texas, “All that changed in 2011, when the state legislature passed the so-called pork chopper law, which allowed hunters to pay to shoot feral hogs out of helicopters – and a new business model was born.” Hunters are happy to pay to hunt, helo companies are happy to take their money, and landowners are happy to have pigs reduced for free. Voila, voluntary exchange creates value…
The United Healthcare Group (UNH) is a gigantic ($260 B market cap, even after recent dip) health plan provider, which until recently seemed to be the bluest of blue-chip companies. It is a purveyor of essential medical services with a wide moat, largely unaffected by tariff posturing, and considered too big to fail. The ten-year stock price chart shows it steadily grinding up and up, shrugging off market tantrums like 2020 and 2022, and even the tragic gunning down of one of its division presidents in December.
But things really unraveled in the past month. Let’s look at the charts, and then get into the underlying causes.
The year-to-date chart above shows the price hanging around $500, then rising to nearly $600 as the April 17 quarterly earnings report approached. Presumably the market was licking its chops in anticipation of the usual UNH earnings beat. The actual report was OK by most corporate standards, but it failed to match expectations. Revenue growth was a hearty +9.8% Y/Y, but this was $2.02B “miss”. Earnings were up 4% over year-ago Q1, but they missed expectation (by a mere 1%). What was probably much more disturbing was guidance on 2025 total adjusted earnings down to $26 to $26.50 per share, compared to $29.74 consensus.
That took the stock down from $600 to around $450 immediately, and then it drifted below $400 in the following month as investors looked for and failed to find better news on the company. But then two things happened last week. The effects are seen in the 1-month chart below:
On May 13 (blue arrow) the company came out with a stunning dual announcement. It noted that the recently-appointed CEO, Andrew Witty, had suddenly resigned “for personal reasons.” The blogosphere speculated (perhaps unfairly) that you don’t suddenly resign from a $25 million/year job unless your “personal reasons” involve things like not going to prison for corporate fraud. The other stunner was that the company completely yanked 2025 financial guidance, due to an unexpected rise in health care costs (i.e., what they must pay out to their participants). Over the next day or two, the stock fell to about 50% of its value in early April.
Then on May 14 the Wall Street Journal came out with an article claiming that the U.S. Department of Justice is carrying out a criminal investigation into UNH for possible Medicare fraud, focusing on the company’s Medicare Advantage business practices. The WSJ said that while the exact nature of the allegations is unclear, it has been an active probe since at least last summer.
UNH promptly fired back a curt response to the “deeply irresponsible” reporting of the WSJ:
We have not been notified by the Department of Justice of the supposed criminal investigation reported, without official attribution, in the Wall Street Journal today.
The WSJ’s reporting is deeply irresponsible, as even it admits that the “exact nature of the potential criminal allegations is unclear.” We stand by the integrity of our Medicare Advantage program.
The stock nose-dived again (red arrow, above), touching 251, as investors completely panicked over “Medicare fraud.” Cooler heads promptly started buying back in, leading to substantial recovery. That includes the new CEO, Steven Hemsley, who was the highly-paid CEO from 2009 to 2017, and since then has been the highly-compensated “executive chairman of the board”, a role created just for him. Pundits were impressed that he stepped in to buy some $25 million of UNH stock near its lows, saying wow, he is really putting some skin in the game. Well, not really: the dude is worth over $1 billion (did I mention high compensation of health care execs?), so $25 mill is hardly heroic. He is already up some 12% or a cool $3 million on this purchase, a tidy little example of how the rich become richer.
In last week’s post, I described how short volatility funds work. They are short (as opposed to long) near-term VIX futures. This means that when a market panic hits and VIX (as measure of volatility) spikes, the prices of these short vol funds plunge, along with stock prices. But as optimism returns to the markets, prices of short vol funds start to recover, as do stocks.
Thus, both short vol funds and general stock funds are reasonable ways to play a market panic. If (!!!) you manage to call the bottom and buy there, you can hold for maybe a couple of weeks until prices recover, and then sell at a profit. I tried to do just that with the market meltdown last month in the wake of the president’s tariff ultimatums: I bought some short vol funds (SVXY, which is a moderate -0.5X VIX fund, and the more aggressive -1X fund SVIX), and also some leveraged stock funds. I discussed leveraged funds here.
I chose to buy into SSO, a 2X leveraged S&P 500 stock fund, whose daily price moves up (or down) by twice the percentage as does the S&P. Obviously, if you think stocks will go up say 10% in the next month, you will make more money by buying a fund that will go up 20% instead, which is why I bought a 2X fund rather than a plain vanilla (1X) stock fund. A related fund, which I did not buy this time, is UPRO, which is a 3X stock fund.
Things are always clear in hindsight. After the smoke of battle clears, you can see right where the bottom was. But it is not clear when you are in the thick of it. I erred by committing much of my dry powder trading funds too early, maybe halfway through the big drop. C’est la vie. It’s hard to improve on that for next time. But a significant learning, that I will act on during the next panic, was how differently short vol versus leveraged stocks recovered from the crash. They both plunged and recovered, but leveraged stocks recovered much better.
It turns out that much of the time, the price movements over say a six-month period of SVXY and SSO largely match each other, so these are useful for comparisons for trading short vol versus leveraged stocks. For instance, below is a chart of SVXY (orange line) and SSO (green line) over the past six months or so. The blue arrow notes the April crash, which bottomed roughly April 8. For November through early April, the price movements of the two funds roughly matched. By April 8, both had plunged to a level some 35% lower than their starting prices. However, by May 12, SSO had recovered to -10% (relative to starting), which is about where it was in late March (green level line drawn in). SVXY, however, remained 21% below its start.
Chart of SVXY ( -0.5X VIX ETF, Orange line) and SSO (2X Stock fund, green line), Nov 2024-May 2024. Blue arrow marks April 2025 volatility spike/stock crash. Chart from Seeking Alpha.
Thus, from its nadir (-35%) to its recovery as of Tuesday, May 12, SSO gained by 38% (i.e., ratioing 0.90/0.65), whereas SVXY gained only 21% (from ratioing 0.79/0.65). Also, it looks like SVXY will not regain its earlier price levels any time soon. So SSO looks like the winner here.
We can do a similar comparison between the -1X VIX fund SVIX and the 3X stock fund UPRO. These two funds are plotted below, along with a plain (1X) S&P 500 stock fund, SPY (in blue). SVIX (orange) and UPRO (green) trend pretty closely for October through March. When the April crash came, SVIX dropped much harder, down to a heart-stopping -59%, compared to -44% for UPRO. SPY dropped only to -15%. SPY comes to a full recovery (0%) by May 12, while UPRO recovers only to -13% [1]. SVIX has recovered only to -21%. If you managed to buy each of these funds on April 8, and sold them today, you would have made the following gains:
SPY 17% ; UPRO 55%; SVIX 43%. Clearly the winner here in short term trading of the April crash is the 3X stock fund UPRO.
Chart of SVIX ( -1X VIX ETF, Orange line), UPRO ( 3X Stock fund, green line), and SPY (1X Stock fund, blue line), Oct 2024-May 2024. Chart from Seeking Alpha.
As a cross check, below is a plot of SVXY (orange) and SSO (green) covering the August, 2024 volatility spike. This was a peculiar event, discussed here, where volatility went crazy for a couple of days, while stock prices experienced only a moderate drop. If (!!!) you timed it just right, and bought at the bottom and sold a week or so later, you could have made good money on SVXY. But zooming out to the larger picture, SVXY never came close to recovering its old highs, whereas SSO just kept going up and up (green arrow). So SSO seems like a safer trading vehicle: it is a reasonable buy-and-hold, whereas SVXY may be hazardous to your portfolio’s health if you don’t get the timing perfect.
Chart of SVXY ( -0.5X VIX ETF, Orange line) and SSO ( 2X Stock fund, green line), Oct 2023-Oct 2024. Blue arrow marks early August 2024 volatility spike. Chart from Seeking Alpha.
Over certain longer (say one-year) periods, there are regimes where short vol could out-perform leveraged stocks (discussed earlier), but that is the exception, rather than the rule.
Disclaimer: Nothing here should be considered advice to buy or sell any security.
ENDNOTE
[1] While UPRO changes X3 the change of SPY on a daily basis, for reasons discussed earlier, the longer-term performance of UPRO diverges from a simple X3 relationship with SPY. In volatile times, UPRO tends to fall well below a 3X performance over say a six-month period.
The VIX is a calculated measure of stock market volatility, based on the prices of stock options. It spikes up when there is a market upset, then seemingly always settles back down again after a few days or weeks. So, it seems simple to make a quick profit from this behavior: short the VIX when it spikes, and then close your trade when it comes back down. What could possibly go wrong?
VIX Index, May 2024-April 2025. From Seeking Alpha.
It’s a bit more nuanced than that, since you can’t directly buy or sell the VIX. It is just a calculated number, not a “thing.” However, there is a market for VIX futures. The value of these futures is based on expectations for what VIX will be on some specific date. The values of these futures go up and down as the VIX goes up and down, though there is not an exact 1:1 relationship. There are funds that short VIX futures, which are a proxy for shorting the VIX futures yourself. So, the individual investor could buy them after the VIX spikes (which would drive down the short VIX fund price), then sell them when VIX declines (and the short VIX fund goes back up).
The chart below shows the VIX (% change, orange curve) in the past twelve months prior to May 1. There were three episodes (Aug 2024, Dec 2024, Apr 2025) where VIX spiked up. These episodes are marked with green arrows. As expected, when VIX spikes up, the short volatility fund SVIX (purple line) drops down. In August and December, if you were clever enough to buy SVIX at its low, you could turn around and sell in a week later for a good profit. The movements of SVIX are dwarfed this plot by the gyrations of VIX in this chart, but a couple of short red horizontal lines are drawn at the bottoming values for SVIX, to show the subsequent rise. A 3x leveraged S&P 500 fund, UPRO, is shown in blue.
There are important nuances with these funds. One is that a long or short VIX futures fund, at the end of the trading day, must buy and sell some futures shares to meet their performance mandate. As of say May 1, the -1X VIX fund SVIX was short 14,311 May VIX futures contracts (expiring 5/20/2025), and short 10,222 June futures (exp. 6/17/2025). To keep its exposure centered at on one month out from the present date, the fund must buy back some near month (here, May) contracts each day, and short some additional next month (June), at the close of every trading day. If the market value of the near month VIX futures contract is lower than the next month contract (being in “contango”), as it generally is during periods of low volatility, this rolling process makes money every day, to the tune of maybe 5% per month. That compounds big time over time, to over a 60% gain in twelve months. That’s the good side. The VIXcentral site shows current and historical VIX futures prices for the next several months out.
A bad side of these short funds is that the day-to-day inverse movements can rachet the fund value down and down, as VIX goes up and down. So even if the VIX ends up in six months at the same value as it is today, it is possible for a short VIX fund to be lower or higher. This can lead to a more or less permanent step down in fund value. Also, in volatile times, the near futures price is higher than the next month out, and so the daily roll works against you.
There is a term that trading pros use for amateurs who jump into volatility funds without really knowing what they are doing: “volatility tourists”. These hapless investors sometimes hear of big profits that have been made recently in vol, and then buy in, often at what turns out to be the wrong time. Then market storms arise, things don’t go the way they expected, and they get shipwrecked.
Such was the case in 2018. SVXY at that time was a fund that moved inversely to volatility futures, on a -1X daily basis. This short vol trade made insane profits in 2H 2016 and in 2017, far outpacing stocks. Someone who bought into SVXY at the start of 2017 would have quintupled their money by the end of the year. (See chart below, orange line).
However, February 5, 2018 is a day that will live in volatility infamy. Because of the roaring success of short VIX in the previous two years, investors had piled into short VIX ETFs. The VIX suddenly doubled that day, and the short vol funds could not do the daily futures trades they needed, and so their value was decimated. This event is known as Volmageddon. The chart below shows the rise (and fall) of the -1X VIX fund SVXY in orange, compared to a stodgy S&P 500 fund SPY (in green).
Folks who bought SVXY looked like geniuses, until Feb 5. Then they lost it all, more or less. The tourists licked their wounds and moved on, and short vol went clean out of fashion for a while. One short VIX fund, XIV, actually an exchange traded note (ETN), went to zero and closed. SVXY itself lost over 90% of its value. After this near-death experience in 2018, SVXY contritely modified its charter from being -1X VIX futures to being -0.5X. That reduces its exposure to vol shocks. That modification served it well in March, 2020 when the world shut down and VIX shot to the moon and stayed there for some time. SVXY lost something like 70% of its value then, but it lived to trade another day, and slowly clawed its way back.
However, short vol has made a comeback in recent years. The -0.5X SVXY was joined in mid-2022 with a new -1X VIX fund, SVIX (for investors who don’t remember what happened to -1X funds in 2018! ). Short vol actually had a very good run in 2022, 2023, and first half of 2024:
The chart above shows SVIX ( -1X, purple) and SVXY (-0.5X, blue), along with the S&P500 (stodgy orange line) over the past three years. The two inverse vol funds totally smoked the S&P through July, 2024. Investors in SVIX were up over 300%, compared to 35% in stocks. Even the more conservative vol fund SVXY was up 165%. Yee-haw!
The volatility tourists poured in, and then came August 5, 2024, with a short, sharp, unexpected spike in volatility. As we noted earlier, it was not so much that stocks cratered, but there was a hiccup in the global financial system, mainly around unwinding of the yen carry trade. The values of the short vol funds got decimated. Then the recent brouhaha over tariffs in April 2025 whacked them again. This drove the value of SVIX below the three-year rise in stocks, although SVXY still outpaces stocks (57% vs 35% rise).
There were dips in SVIX and SVXY in March 2023 (Silicon Valley Bank blowup), October 2023 (Yom Kippur attacks on Israel by Hamas), and April, 2024, corresponding to spikes in VIX. In those cases, it worked great to buy the dip, since within a few months SVIX and SVXY churned to new highs. Many were the articles in the investing world on the wonderful virtues of the daily VIX futures roll. But then August 2024 and April 2025 hit, where there was no complete, rapid recovery from the huge price drops.
What to take away from all this? What comes to my mind are well-worn truisms like:
If it looks too good to be true, it’s probably not true; There is no free lunch on Wall Street; It’s not different this time.
The reason I know this much about these trading products is that I got sucked in a bit by the lure of monster returns. Fortunately, I kept my positions small, and backstopped some trades by using options, so all in all I have probably roughly broken even. That is not great, considering how much attention and nail-biting I have put into short vol trading in the past twelve months.
In an upcoming post, I will report on an alternative way to trade volatility spikes, which has worked out much better.
Disclaimer: Nothing here should be considered advice to buy or sell any security.
Chickens were apparently domesticated from the red jungle fowl (Gallus gallus), a native of southeast Asia, thousands of years ago. Humans have been selectively breeding them ever since. Traditionally, chickens were valued mainly for their eggs. Surplus roosters would get eaten, of course, and tough overage laying hens would end up in the stewpot. But your typical chicken was a stringy, hardy bird whose job was to stay alive and to lay eggs.
Raising chickens en masse just for eating started in 1923 with Celia Steele of southern Delaware, somewhat by accident. She wanted to set up a small flock of egg-laying chickens to supplement her husband Wilmer’s Coast Guard salary. She placed an order for 50 chicks, but it was mistakenly heard as 500. When she got this huge shipment, she thought fast and decided to raise them to eating size (“broilers”) and then immediately sell them. She built a coop designed for grow-out, rather than for egg-laying. This enterprise was profitable, so she expanded operations. She doubled production the next year, and by 1926 she had 10,000 chickens. Her neighbors saw her success, and also went into the broiler biz. Thus was spawned the modern broiler industry. All this was aided by the general prosperity in the 1920s, together with technical progress in refrigeration and transportation. Her first broiler house is now on the U.S. Registry of Historic Places.
However, chickens themselves were still scrawny by today’s standards. As of 1948, chicken meat was still an expensive luxury. With the broiler (meat chicken) market established, breeders naturally tried to develop strains that would grow big and fast. That not only allows more meat to be grown in a given flock, but fast growth means less feed is consumed to get to market weight.
For several years around 1950, A&P Supermarkets sponsored a “Chicken of Tomorrow” program, overseen by the USDA, to promote improved broiler breeding. As examples of chickendom as of 1948, here are plucked carcasses of contestants for the Chicken of Tomorrow contest of that year. Note how stringy they are, compared to the plump, meaty bird you buy at the grocery store today:
Without going into much detail, the ultimate product was a cross (hybrid) between the Cornish chicken and other breeds. Cornish cross chickens were initially bred for size and growth rate. By say the 1990s, that led to birds that were so heavy that they sometimes could not support their own weight. More recent breeding programs promote leg strength and other health factors, as well as sheer growth.
To produce today’s optimized broiler is a complex process. Breeders must maintain something like four purebred strains, and then carefully cross-breed them, and then cross-breed some more, to get the final hybrid chick to send out for farmers to raise. Only these hybrids have the optimized characteristics; you can’t just take a bunch of these crossed chickens and breed a good flock from them:
Only a few large outfits can afford to do this, so most hatcheries are supplied by a handful of big breeders. However, there seems to be enough competition to keep the prices down for the consumer. Some folks will always find something to complain about (reduced genetic diversity or hardiness, etc.), but they are welcome to breed and grow less efficient chickens, if it pleases them.
In terms of dollars: “The inflation-adjusted cost of producing a pound of live chicken dropped from US$2.32 in 1934 to US$1.08 in 1960. In 2004, the per-pound cost had dropped to 45 cents, according to the USDA Poultry Yearbook (2006).”
According to the National Chicken Council, in 1925 it took a broiler chicken an average of 112 days to reach a market weight of 2.5 pounds. As of 2024, the market weight has soared to 6.5 pounds, and chickens reach that weight much faster, in 47 days (about the time it takes leafy green vegetables). The net result is that now it only takes about 1.7 pounds of feed to grow one pound of chicken, compared to 4.7 lb/lb in 1925. This nearly three-fold reduction in resource consumption translates into lower consumer costs, lower load on the environment and agricultural resources, and even lower CO2 generation. The largest jump feed conversion efficiency (from 4 to 2.5 lb/lb) occurred between 1945 and 1960, thanks to the development of the Cornish cross.
Despite the nearly universal outcry, President Trump was standing firm on his massive tariffs. “No backing down”, etc., despite the evaporation of trillions of dollars in stock values. On Tuesday, April 8, White House spokesperson Karoline Leavitt affirmed: “The President was asked and answered this yesterday. He said he’s not considering an extension or delay. I spoke to him before this briefing. That was not his mindset. He expects that these tariffs are going to go into effect.” However, the next day, Wednesday, April 9, Trump announced on his social media platform, Truth Social, that for all countries but China, there would be a 90-day pause in reciprocal tariffs.
What happened here? The common explanations are that (1) the chaos and losses in the markets had finally grown intolerable, or that (2) the president had planned all along to pause the tariff hikes on April 9. I suspect there is some merit to both of these factors – -despite all the prior warnings, I think (1) Trump did not expect such market devastation (he sincerely believes that he is making the American economy great, so why should markets crash?), and also (2) that he had indeed planned to play around with tariff implementations in pursuit of deals.
But what some analysts pointed out as a further factor was the drop in the market value of U.S. Treasury bonds, which correlates directly to a rise in interest rates. The actions of the Administration have seemingly caused market participants, especially abroad, to question the risk-free status of U.S. debt. If the government has to pay higher interest on its debt, it is game over, as interest payments will spiral up and consume an ever-higher share of the federal budget. The chart below shows in orange the price movement of the TLT fund, which holds long-term T-bonds, plummeting on April 7, 8, and 9 (red arrow), as an indicator of rising rates. TLT price then shot upwards, along with stocks (the green line is S&P 500 fund SPY) late on April 9, in the relief following the tariff announcement:
As Treasury Secretary, Scott Bessent would be particularly sensitized to the interest rate issue, and able to communicate that to the boss. He has been a successful hedge fund trader and manager, so he understands the plumbing of the system, unlike some other presidential advisors. Up till then, however, economist Peter Navarro, who is ultra-hawkish on tariffs, had had the ear of the president.
So, what did Bessent do? (This is the part that only came to my attention a few days ago, even though technically this is old news). It seems he enlisted the support of Commerce Secretary Lutnick, and adroitly chose a time when Navarro was tied up in a meeting, and barged in on the president in an unscheduled meeting so they could get him alone. And it worked! Evidently, they persuaded him that now was the time to do the clever deal-making thing and issue a pause. It’s a mark of how readily the president can change his mind that his own press spokespeople were unaware of this volte-face, and had to scramble to make sense of it. It is also interesting that cabinet members are resorting to cloak-and-dagger tactics to get policy done.
Bessent naturally gave all the credit to the president for the decision, but he and Lutnick had photos taken to show who saved the financial world – for now:
Scott Bessent (standing, left) and Howard Lutnick (right) with President Trump as he signs 90-day pause in reciprocal tariffs. Source: Daily Mail.
The president’s recent musings about trying to fire the supposedly independent Fed chairman have since contributed to interest rates going back up again, but that is another story.
Economist Writing Every Day 