How a Protective Options Collar Cushioned a Loss in Korean Stock Fund EWY

After being convinced by a series of favorable articles, I bought a few shares last month of the EWY fund, which holds shares of major South Korean companies. The narrative seemed compelling: the vast production of compute processing chips for AI has led to a structural supply shortage of fast memory chips. South Korean firms excel in making these chips, and so high, growing profits seemed assured. What could possibly go wrong?

What I didn’t know was that thousands of other retail investors were thinking the exact same thing, and hence had bid the price of EWY up to possibly unreasonable levels. Somehow, my bullish analysts missed that point. In particular, the South Korean market is driven by an unusually high level of margin trading, where investors borrow money on margin to buy shares. A market drop leads to margin calls, which leads to forced selling, which really crashes prices.

The other thing I did not know was that, two days after my purchase, the attacks on Iran would commence. Oops. Among other things, this would drive up the world price of oil, which impacts energy importers like South Korea. This seems to have been the trigger for the sharp stock drop.

Here is the six-month price chart for EWY:

As it happened, I bought pretty much at the top, and as of Monday midday when I am writing this, EWY was down about 17%. That doesn’t look like much of a drop on the chart, because of the long run-up to this point, but it is an unpleasant development if you just bought in two weeks ago.

Fortunately, when I bought the EWY shares, I set up a protective options collar, since this was not a high conviction buy. First, I bought a put with a strike price about 7% below my purchase price, which would limit my maximum loss on the EWY shares to 7%. A problem is that this put cost serious money (about 11% of the share price), so my maximum loss could actually be 7% plus 11% = 18%. Therefore, I offset nearly all the cost of the put by selling a call with a strike price about 17% above the current EWY share price. That meant that I could profit from a rise in EWY share price by up to 17%, while being protected against a drop of more than 7%. That seemed like a favorable asymmetry (7% max loss vs 17% max gain).

This arrangement (buying a protective put to limit downside, financed by selling a call which limits upside) is called an options “collar”. I’d rather accept a limited upside than have to worry about doing clever trading to mitigate a big loss.

As of Monday, my collar was working well to protect the overall position. As might be expected, the value of my put increased, with the drop in EWY share price. But also, the value of my call decreased, which further helps me, since I am short that call. The net result was that about 75% of the loss in the stock price was compensated by the changes in values of the two options.

This is just a small, experimental position, but it was nice to see practical outcomes line up with theory.

Disclaimer: As usual, nothing here should be considered advice to buy or sell any security.

 Autism Is Largely Genetic (Not Environmental)

Autism is a condition that can cause enormous anxiety and grief, especially for parents of autistic children. The economic implications are also considerable. A 2021 study by Blaxill, et al., estimated the annual costs to society of autism in the U.S. to be $223 billion in 2020, $589 billion in 2030, $1.36 trillion in 2040, and an astonishing $5.54 trillion by 2060.

 The rising diagnosis rates are sometimes attributed to changes in environmental factors or diets. It is obviously essential to get the science right on this. Here I will summarize an article by epidemiologist Mark Strand, “Understanding Autism Spectrum Disorder Epidemiologically and Theologically”. This article was published on the Biologos web site on January, 2026. The author addresses the medical aspects sand also the moral aspects. Upfront disclaimer: I have no expertise in this area; I am just trying to faithfully convey the scientific consensus.

The Myth of the “Autism Epidemic”

The article begins by addressing a common misconception: that autism is experiencing a sudden, alarming surge in cases—an “epidemic.” This idea gained traction when the current administration announced a “massive testing and research effort” to identify environmental causes behind the rise. But as the author explains, this framing is scientifically inaccurate.

Autism is not an acute condition like strep throat or a viral outbreak. It’s a lifelong neurodevelopmental disorder that emerges during early brain development, typically between ages two and four.  Unlike infectious diseases that appear suddenly and resolve quickly, autism is chronic and complex. The term “epidemic” refers to a rapid, atypical increase in cases—something that doesn’t align with the actual data.

In 2022, the CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network reported 32.2 cases of ASD per 1,000 children. This is massive (fourfold) increase from two decades ago.  But this rise isn’t due to a sudden environmental trigger. Instead, it reflects broader diagnostic criteria, increased public awareness, better screening practices, and greater access to services:

While this increase may seem alarming at first glance, it is widely accepted that it largely reflects changes in the definition used for ASD and the importance placed on ASD by society and educational systems.

Since it was first recognized as a condition in the Diagnostic and Statistical Manual of Mental Disorders (DSM), the definition for ASD has been broadened several times. This included combining a cluster of related neurological disorders into one disorder, relaxing the age of onset, and better classifying the presentation of autism in girls and children of color, leading to more accurate, but higher, numbers.

States like California and Pennsylvania, which have robust early intervention systems and strong Medicaid coverage for autism services, report the highest prevalence rates.

Genetics Over Environment: The Scientific Consensus

One of the most critical points the article makes is that autism is primarily genetic.  Twin studies show that if one identical twin has autism, the other twin has a 60% to 90% chance of also having it. A large Swedish study of over 37,000 twins found that 83% of autism cases could be attributed to genetics.

While environmental factors may play a role, the evidence is far from conclusive. The article debunks popular myths—like the claim that acetaminophen (Tylenol) use during pregnancy causes autism. High-quality studies, including one of 2.5 million children in Sweden with sibling controls, found no link between prenatal acetaminophen use and autism risk.  Similarly, the idea that vaccines cause autism has been thoroughly discredited by decades of rigorous research.

The real danger lies in chasing unproven causes—a practice that wastes resources and distracts from meaningful science.  Instead, researchers should focus on gaps in knowledge using the scientific method: building on what we know, forming new hypotheses, and testing them rigorously.

The Spectrum of Experience: Diversity, Not Deficit

Autism is not a monolithic condition. It exists on a spectrum, ranging from individuals with significant support needs to those with high intelligence and exceptional skills.

The article highlights some striking statistics:

  • 14% of autistic individuals graduate from college, compared to 32% of the general population.
  • Among college graduates with autism, 34.3% major in STEM fields, significantly higher than the 22.8% in the general population.

These numbers challenge the harmful stereotype that autistic people are universally disabled or burdensome. Many autistic individuals thrive in science, technology, engineering, and mathematics—fields that value pattern recognition, attention to detail, and deep focus.

Yet, challenges remain. Social communication difficulties, restricted interests, and repetitive behaviors can be isolating. Early intervention—especially for those with moderate to mild autism—can make a meaningful difference in socialization and quality of life.

A Call for Grace, Truth, and Inclusion

The article concludes by noting that autism is not a tragedy, but a part of human diversity. It calls on society at large to respond with truth, grace, and care—not fear or stigma.

The article notes: “It is not a good use of resources to repeat studies on well-established scientific evidence or chase popular beliefs about supposed causes.” Rather than searching for a single cause to “eliminate,” we should focus on understanding, supporting, and empowering autistic people.  This includes investing in early screening, improving access to therapy, and promoting inclusive education and employment.

The rise in autism diagnoses is not a crisis to panic about—it’s a call to do better with better science, better policies, and better compassion. By grounding our understanding in data, embracing neurodiversity, and responding with love, we can build a world where autistic individuals are not just accepted—but valued.

MORE ON GENETIC CAUSATION OF AUTISM

I was curious, so I did a little more digging, beyond Dr. Strand’s article, on the roots of autism. Here are couple of quotes from the UCLA David Geffen School of Medicine, home of Dr. Daniel Geschwind, who won a National Academy of Medicine prize for investigating autism’s genetic underpinnings:

Autism is hereditary and therefore does run in families. A majority (around 80%) of autism cases can be linked to inherited genetic mutations. The remaining cases likely stem from non-inherited mutations. 

There’s no evidence that children can develop autism after early fetal development as a result of exposure to vaccines or postnatal toxins.  “Everything known to cause autism occurs during early brain development,” says Dr. Geschwind.

A NOTE ON TREATMENTS FOR AUTISM

Some articles on autism seem to convey that it is a condition that someone is simply stuck with for the rest of their lives, with maybe a brief nod to “therapies”. But this situation is maybe not quite so grim, at least for some children on the spectrum. My browser AI summarizes the situation as:

Therapy for autism can be highly effective, particularly when started early and tailored to the individual’s needs. Evidence-based therapies such as Applied Behavior Analysis (ABA)speech therapyoccupational therapy (OT), and physical therapy (PT) are widely recognized for improving communication, social skills, daily living abilities, and reducing challenging behaviors. 

And, anecdotally, I know a board-certified behavior analyst (BCBA) who has reported seeing significant improvements with autistic children upon treatment. Early, skilled therapy can often reshape a child’s behavioral habits enough to allow them to function in mainstream society.

Sleigh or Sled Shovels: Move Lots of Snow with No Lifting

Now that we have your attention (if you just got buried in a blizzard yesterday), let’s talk about shoveling snow. Everyone knows how a standard snow shovel works. You bend down, with one hand on the end of the handle and the other hand halfway along the handle, you shove forward, load up the shovel blade, then (Ooof!) lift it up and throw the snow where it needs to go. For many of us, this action uses muscles and joints that are not conditioned for it. Fun facts: every year some 100 Americans die from shoveling snow, and another 11,000 or so end up in the emergency room.

Is there a better way? Well, a powered snowblower can work. But that doesn’t fit everyone’s situation. It turns out there is a better way to manually shovel snow, that fits many (not all) situations.

As I was reading about “electric snow shovels” (more on that another time), I ran across mention of “sleigh shovels” or “sled shovels” or “snow scoops.” Apparently, they are very widely used by Canadians and Alaskans, who ought to know something about snow. A genius aspect of these shovels is that you never have to lift them.

Here is a picture of a 24” Garant brand sled shovel:

Source: Ace Hardware   

Here’s how they work: Start with the position shown, shove it forward (you get to use both hands out in front of you, in an ergonomically good position), till the scoop is largely filled with snow. Then, tilt it back a little, and push this load forward, sledding along until you get to the edge of the driveway. Keep pushing it another several feet, out onto the lawn. Then dump the snow off the shovel by a quick shove forward and a sudden jerk back, to pull the shovel out from under the snow. Plan your dumping points so as to get a gradual ridge beside the driveway, not a narrow, high ridge right at the edge.

Here is a 47-second video demo, on a small scale.

Take a quick look at 1:40 – 3:40 (two minutes) of this video to see a more challenging situation (deep snow, big existing ridge on edge). This shows that one scoop shovel-full is equivalent to more than three regular shovel-fulls, and this snow is expelled from the driveway with NO LIFTING. It’s beautiful! Here are two screen shots from this video:

Garant seems to be the most well-established brand here. ACE hardware (see photo above) is selling them for $70. On Amazon, I see a Garand model being sold for an eye-watering $266, maybe scalping prices for the latest blizzard. That is a lot of money for a plastic scoop with a metal handle. You can probably do better by shopping elsewhere or at a different time.

I am tempted to get one, but I don’t have a wide driveway with grassy dumping areas on the sides. I have to shovel mainly steps and narrow sidewalks, often with wet, slushy, not super deep snow. Sleigh shovels can work in these situations, but their advantages are muted, compared to the deep powdery snow found in colder regions.

But if I were living in Boston or Providence or New York, a sleigh shovel would be mighty handy right now.

Broad Slump in Tech and Other Stocks: Fear Over AI Disruption Replaces AI Euphoria

Tech stocks (e.g. QQQ) roared up and up and up for most of 2023-2025, more than doubling in those three years. A big driving narrative was how AI was going to make everything amazing – productivity (and presumably profits) would soar, and robust investments in computing capacity (chips and buildings), and electric power infrastructure buildout, would goose the whole economy.

Will the Enormous AI Capex Spending Really Pay Off?

But in the past few months, a different narrative seems to have taken hold. Now the buzz is “the dark side of AI”. First, there is growing angst among investors over how much money the Big Tech hyperscalers (Google, Meta, Amazon, Microsoft, plus Oracle) are pouring into AI-related capital investments. These five firms alone are projected to spend over $0.6 trillion (!) in 2026. When some of this companies announced greater than expected spends in recent earning calls, analysts threw up all over their balance sheets. These are just eye-watering amounts, and investors have gotten a little wobbly in their support. These spends have an immediate effect on cash flow, driving it in some cases to around zero. And the depreciation on all that capex will come back to bite GAAP earnings in the coming years, driving nominal price/earnings even higher.

The critical question here is whether all that capex will pay out with mushrooming earnings three or four years down the road, or is the life blood of these companies just being flushed down the drain?  This is viewed as an existential arms race: benefits are not guaranteed for this big spend, but if you don’t do this spending, you will definitely get left behind. Firms like Amazon have a long history of investing for years at little profit, in order to achieve some ultimately profitable, wide-moat quasi-monopoly status.  If one AI program can manage to edge out everyone else, it could become the default application, like Amazon for online shopping or Google/YouTube for search and videos. The One AI could in fact rule us all.

Many Companies May Get Disrupted By AI

We wrote last week on the crash in enterprise software stocks like Salesforce and ServiceNow (“SaaSpocalypse”). The fear is that cheaper AI programs can do what these expensive services do for managing corporate data. The fear is now spreading more broadly (“AI Scare Trade”);  investors are rotating out of many firms with high-fee, labor-driven service models seen as susceptible to AI disruption. Here are two representative examples:

  • Wealth management companies Charles Schwab and Raymond James dropped 10% and 8% last week after a tech startup announced an AI-driven tax planning tool that could customize strategies for clients
  • Freight logistics firms C.H. Robinson and Universal Logistics fell 11% and 9% after some little AI outfit announced freight handling automation software

These AI disruption scenarios have been known for a long time as possibilities, but in the present mood, each new actual, specific case is feeding the melancholy narrative.

All is not doom and gloom here, as investors flee software companies they are embracing old-fashioned makers of consumer goods and other “stuff”:

The narrative last week was very clearly that “physical” was a better bet than “digital.” Physical goods and resources can’t be replaced by AI like digital goods and services can be at an alarming rate

As I write this (Monday), U.S. markets are closed for the holiday. We will see in the coming week whether fear or greed will have the upper hand.

SaaSmageddon: Will AI Eat the Software Business?

A big narrative for the past fifteen years has been that “software is eating the world.” This described a transformative shift where digital software companies disrupted traditional industries, such as retail, transportation, entertainment and finance, by leveraging cloud computing, mobile technology, and scalable platforms. This prophecy has largely come true, with companies like Amazon, Netflix, Uber, and Airbnb redefining entire sectors. Who takes a taxi anymore?

However, the narrative is now evolving. As generative AI advances, a new phase is emerging: “AI is eating software.”  Analysts predict that AI will replace traditional software applications by enabling natural language interfaces and autonomous agents that perform complex tasks without needing specialized tools. This shift threatens the $200 billion SaaS (Software-as-a-Service) industry, as AI reduces the need for dedicated software platforms and automates workflows previously reliant on human input. 

A recent jolt here has been the January 30 release by Anthropic of plug-in modules for Claude, which allow a relatively untrained user to enter plain English commands (“vibe coding”) that direct Claude to perform role-specific tasks like contract review, financial modeling, CRM integration, and campaign drafting.  (CRM integration is the process of connecting a Customer Relationship Management system with other business applications, such as marketing automation, ERP, e-commerce, accounting, and customer service platforms.)

That means Claude is doing some serious heavy lifting here. Currently, companies pay big bucks yearly to “enterprise software” firms like SAP and ServiceNow (NOW) and Salesforce to come in and integrate all their corporate data storage and flows. This must-have service is viewed as really hard to do, requiring highly trained specialists and proprietary software tools. Hence, high profit margins for these enterprise software firms.

 Until recently, these firms been darlings of the stock market. For instance, as of June, 2025, NOW was up nearly 2000% over the past ten years. Imagine putting $20,000 into NOW in 2015, and seeing it mushroom to nearly $400,000.  (AI tells me that $400,000 would currently buy you a “used yacht in the 40 to 50-foot range.”)

With the threat of AI, and probably with some general profit-taking in the overheated tech sector, the share price of these firms has plummeted. Here is a six-month chart for NOW:

Source: Seeking Alpha

NOW is down around 40% in the past six months. Most analysts seem positive, however, that this is a market overreaction. A key value-add of an enterprise software firm is the custody of the data itself, in various secure and tailored databases, and that seems to be something that an external AI program cannot replace, at least for now. The capability to pull data out and crunch it (which AI is offering) it is kind of icing on the cake.

Firms like NOW are adjusting to the new narrative, by offering pay-per-usage, as an alternative to pay-per-user (“seats”). But this does not seem to be hurting their revenues. These firms claim that they can harness the power of AI (either generic AI or their own software) to do pretty much everything that AI claims for itself. Earnings of these firms do not seem to be slowing down.

With the recent stock price crash, the P/E for NOW is around 24, with a projected earnings growth rate of around 25% per year. Compared to, say, Walmart with a P/E of 45 and a projected growth rate of around 10%, NOW looks pretty cheap to me at the moment.

(Disclosure: I just bought some NOW. Time will tell if that was wise.)

Usual disclaimer: Nothing here should be considered advice to buy or sell any security.

After the Crash: Silver Clawing Back Up After Epic Bust Last Week

A month ago (red arrow in 5-year chart below), I noticed that the price of silver was starting into a parabolic rise pattern. That is typical of speculative bubbles. Those bubbles usually end in a bust. Also, the rise in silver price seemed to be mainly driven by retail speculators, fueled by half-baked narratives rather than physical reality.

Five-year chart of silver prices $/oz, per Trading View

So I wrote a blog post here last month warning of a bubble, and sold about a quarter of my silver holdings. (I also initiated some protective options but that’s another story for another time.) I then felt pretty foolish for the next four weeks, as silver prices went up and up and up, a good 40% percent over the point I initially thought it was a bubble. Maybe I was wrong, or maybe the market can stay irrational longer than you can stay solvent, per J. M. Keynes.

When the crash finally came, it was truly epic. Below is a one-month chart of silver price. The two red lines show silver price at the close of regular trading on Thursday, January 29 (115.5 $/oz), and at the close of trading on Friday, January 30 (84.6 $/oz):

This is a drop of nearly 30% in one day, which is a mind-boggling move for a major commodity. Gold got dragged down, too:

These aren’t normal moves. Over roughly the past 25+ years (through 2025), gold’s price has changed by about 0.8% per day on average (in absolute percentage terms). Silver, being more volatile, has averaged around 1.4–1.5% per day. If you’re scoring at home, that’s about a 13 Sigma move for Gold and 22 Sigma move for Silver! You’re witnessing something that shouldn’t happen more than once in several lifetimes…statistically speaking. Yet here we are.

After the fact, a number of causes for the crash were proposed:

  • The nomination of Kevin Warsh as the next Federal Reserve Chair.  Warsh is perceived as a hawkish policymaker, leading investors to expect tighter monetary policy, higher interest rates, and a stronger U.S. dollar—all of which reduce the appeal of non-yielding assets like silver. 
  • Aggressive profit-taking after silver surged over 40% year-to-date and hit record highs near $121 per ounce. 
  • Leveraged positions in silver futures were rapidly unwound as prices broke key technical levels, triggering stop-loss orders and margin calls. 
  • CME margin hikes (up to 36% for silver futures) increased trading costs, forcing traders to cut exposure and accelerating the sell-off. 
  • Extreme speculation among Chinese investors, leading the Chinese government to clamp down on speculative trading. (And presumably Chinese solar panel manufacturers have been complaining to the government about high costs for silver components).

What happens next?

Silver kept falling to a low of 72.9 $/oz in the wee hours of February 2, a drop of 40% percent from the high of 120.8 on Jan 26. However, it looks to my amateur eyes like the silver bubble is not really tamed yet. For all the drama of a 22-sigma crash one day crash, about all that did was erase one months’ worth of speculative gains. The charts above are showing that silver is clawing its way right back up again.  It is very roughly on the trend line of the past six months, if one excludes the monster surge in the month of January.

There is a saying among commodities traders, that the cure for high prices is high prices. This means that over time, there will be adjustments that will bring down prices. In the case of silver, that will include figuring out ways to use less of it, including recycling and substitution of other metals like copper and aluminum. However, my guess is that the silver bulls feel vindicated by the price action so far, and will keep on buying at least for now.

Disclaimer: As usual, nothing here should be regarded as advice to buy or sell any security.

Economic Impacts of Weather Apps Exaggerating Storm Dangers

Snowmageddon!! Over 20 inches of snow!!! That is what we in the mid-Atlantic should expect on Sat-Sun Jan 24-25 according to most weather apps, as of 9-10 days ahead of time.  Of course, that kept us all busy checking those apps for the next week. As of Wednesday, I was still seeing numbers in the high teens in most cases, using Washington, D.C. as a representative location. But my Brave browser AI search proved its intelligence on Wednesday by telling me, with a big yellow triangle warning sign:

 Note: Apps and social media often display extreme snow totals (e.g., 23 inches) that are not yet supported by consensus models. Experts recommend preparing for 6–12 inches as a realistic baseline, with the potential for more.

“Huh,” thought I. Well, duh, the more scared they make us, the more eyeballs they get and the more ad revenue they generate. Follow the money…

Unfortunately, I did not log exactly who said what when last week. My recollection is that weather.com was still predicting high teens snowfall as of Thursday, and the Apple weather app was still saying that as of Friday. The final total for D.C. was about 7.5 inches for winter storm Fern. In fairness, some very nearby areas got 9-10 inches, and it ended up being dense sleet rather than light fluffy snow. But there was still a pretty big mismatch.

Among the best forecasters I found was AccuWeather. They showed a short table of probabilities that centered on (as I recall) 6-10”, with some chances for higher and for lower, that let you decide whether to prepare for a low probability/high impact scenario. It seems that the Apple weather app is notoriously bad: instead of integrating several different forecast models like some other apps (and like your local talking head meteorologist), it apparently just spits out the results of one model:

The core issue is that many weather apps, including Apple Weather, display raw data from individual forecast models without the context and analysis that professional meteorologists provide. While meteorologists at the National Weather Service balance multiple computer models, dozens of simulations and their own expertise to create forecasts, apps often pull from a single source and deliver it directly to users.

“Everything that catches attention is mostly nonsense,” said Eric Fisher, chief meteorologist for WBZ-TV in Boston. He points to the viral snowfall maps that spread on social media, noting that extreme forecasts generate the most attention even when they may not be the most accurate.

Anyway, I tried to poke around and find out in dollar terms how much it benefits the weather apps to exaggerate storm dangers. I was unsuccessful there, but by playing with query wording, I was able to coax out of ChatGPT some numbers on how much these exaggerations may cost the rest of us. (A more qualitative search noted, among other things, that the “crying wolf” cost of people becoming jaded to alarmist forecasts may lead them to discount genuine warnings; and I will add it is inconvenient to find the stores out of things because of panic buying).

Everything below the line of asterisks is just a straight dump from the AI, since I could not readily improve on its presentation:

****************************************************************

The economic impact of weather apps exaggerating storm dangers isn’t easy to quantify precisely because most formal studies focus on weather warnings overall (from official sources like the National Weather Service), not specifically on private weather apps exaggerating risk. However, economics research on false alarms, over-warning, and exaggerated alerts offers concrete dollar figures that we can use to approximate the kinds of costs involved. Below are the key economic impacts with as many dollar figures as available:


💸 1. Opportunity Costs of False or Overbroad Storm Warnings

Time cost of false warnings:

  • Traditional county-wide tornado warnings (over-broad alerts) have historically forced many people to shelter unnecessarily, resulting in ≈234 million person-hours per year spent under warnings (1996–2004) — valued at roughly $2.7 billion annually in lost time/productivity in the U.S. alone.
  • Improved storm-based warnings that reduce false warning area could save up to $750 million–$1.9 billion/year in avoided lost time.

This demonstrates that exaggerated alerts — such as those sometimes amplified or presented without clear context by weather apps — can force unnecessary economic shutdowns of work and business activity.


🏙️ 2. Evacuation and Preparedness Costs from False Alarms

Evacuation costs:

  • A NOAA analysis estimates that evacuation costs for hurricanes, when done broadly for storm-warnings, can reach about $1.4 billion annually in the U.S., with roughly $1 billion being unnecessary cost due to false alarms (people evacuating where no damaging winds ultimately occur).

Evacuations are one of the most expensive forms of response — from lost wages to lodging and fuel costs — and exaggerated risk messaging can trigger them prematurely or more frequently.


🏭 3. Business Productivity Losses from False Alerts

Example from private sector:

  • A building management firm reported that by reducing false storm alerts (better targeted data rather than broad app warnings), it saved ~$10 million in lost production time in one year alone.

This is a real dollar example showing how over-warning impacts businesses directly when they preemptively shut down operations.


💼 4. Broader Firm-Level Economic Avoidance

Cost avoidance from better warning info:

  • A study of nearly 500 firms found that switching from deterministic (binary “storm/no storm”) warnings to probabilistic information could produce $2.3 billion to $7.6 billion per year in avoided costs for businesses, thanks to better decision-making.

While this doesn’t measure exaggeration specifically, it underscores the economic penalty of imprecise or alarmist warnings, which many weather apps unintentionally echo.


📉 5. Insurance & Property Impacts

Although not directly about exaggerated warnings, inaccurate perceptions of storm danger influence behavior and pricing:

  • Insurance premiums rising: In storm-prone states (e.g., Florida), homeowners’ premiums have risen by ~57% or more because of risk perceptions and loss patterns tied to severe weather.
  • Losses from storms: Billion-dollar disasters are common; for example, Hurricane Milton in 2024 had estimated total costs of $21–$85 billion (depending on source).

While not directly caused by exaggeration, inflated perceptions of danger (from apps or media) can affect insurance markets and property values, contributing indirectly to economic impacts.


📈 6. Net Benefits vs. Exaggeration

It’s important to balance:

  • Early warnings overall clearly save money and lives. Improved forecasts and early alert systems have been estimated to avoid $300 million to $2 billion per year in asset losses and provide up to $32 billion/year in broader economic benefits (through optimized activities and prep).

This highlights that the problem isn’t warnings per se, but inaccurate or exaggerated warnings that cause over-response.

Restraining Sleep Position Can Help Heal Tennis Elbow

Tennis elbow (or these days, pickleball elbow) is a painful, debilitating condition that affects around 2% of adults at any given time. Active tennis players have about a 50% chance of being stricken at some point. If you give it a chance to heal, it usually goes away within a year, but that is a long time to be in pain or disabled.

The traditional technical name for this condition is “lateral epicondylitis.” That suffix “…itis” implies inflammation, but it is now known that typical inflammation markers are generally absent. So, the new jargon is the deliberately ambiguous “tendinosis” or even “tendinopathy.” It seems to be caused by accumulated damage to the very end of the tendon that anchors the muscles which are attached to the back of your hand. Those muscles that let you tilt your hand up; if you grip something hard and try to hold something steady, those muscles contract in a big way. The micro tears seem to occur right about where that tendon attaches to a little knob of bone at the very outside of your elbow joint:

From Wikipedia

This condition is somewhat frustrating for doctors and for patients, since there’s not a single clear effective treatment. Although injecting Cortisone type anti-inflammatories gives short-term pain relief, it seems to adversely affect longer term outcomes, so those shots are less common than 20 years ago. Therapists throw all sorts of techniques at it, including NSAIDs, heat, cold, exercises, braces, shock waves, acupuncture, injections of blood extracts, and so on. All these may help, though for every study that shows positive results for a given treatment there seems to be one that doesn’t.

I have a personal interest in this subject, since I have a long-standing for propensity towards tennis elbow. I had to stop playing tennis many years ago because of it. More recently, I spent the day helping on a work project, installing sheet rock to repair flood damage in a someone’s home. After a day gripping a powered drill driver, the old tennis elbow flared up significantly.

In the course of my internet search, I ran across a very promising study that seems to have been largely neglected. It is also a sweet piece of science.

An orthopedist named Jerrold Gorski started reflecting on the common observation that tennis elbow often feels worst upon waking up in the morning. That made him wonder whether something was going on in the night that caused the condition to worsen. Which led him to hypothesize that tennis elbow might be helped by changing a patient’s sleep posture. Prior studies showed that people spend some 55% of the night sleeping with their arm crooked up overhead, something like this:

That position could keep stress on the tendon all night, and inhibit it from healing. Dr. Gorski also noted that in the literature there are other examples of sleep posture or waking postures making a difference in treating various orthopedic conditions.

And so, like a good scientist, he devised an experiment to test his hypothesis. He came up with a very simple technique of using a bathrobe belt, which is soft and wide, to restrain the arm during sleep. You simply tie a large loop at one end that goes around the thigh, and a smaller loop at the other that fits snuggly around the wrist. If all goes well, this rigging well prevent will keep the arm down close to the side all night, so it cannot get crunched under the head:

Dr. Gorski tried tried this out with 39 tennis elbow patients. Six of them apparently could not tolerate being roped for the night, so they were designated as “treatment failures”, or effectively a control group. The other 33 patients stuck with the protocol, although most of them, like the 6 “treatment failures”, complained about interference with going to sleep or staying asleep.

There was a fairly dramatic difference in outcomes. The six treatment failures had ongoing tennis elbow symptoms that persisted unchanged over the initial 3-month study period. Of the thirty-three patients who stuck with the protocol, 66% reported improvement within 1 month, and 100% of them improved within 3 months. Those are really good results.

Obviously, it’s not a perfect study. It only claims to be a prospective study. Nevertheless, the results were so promising, and the treatment was so inexpensive and harmless and noninvasive, I would’ve thought that it would get a lot of attention. But looking in Google Scholar for citations, I only saw seven articles that cited it. Two of those articles were letters to the editor by the author, Dr. Gorksi himself, seemingly trying to draw due attention to his promising study, and one citation was in an article that got retracted. This leaves only 4 independent citations in the medical literature all of which, as best I could tell, were about touting some other treatment, and just nodded in passing to Dr. Gorski’s work. So, essentially crickets. One can only speculate on why the medical profession has not paid more attention to a treatment which requires nothing more than an office visit and demo with a strip of cloth.

I want to give a shout-out to the UK-based “Sports Injury Physio” website, which, in a very helpful and comprehensive article on tennis elbow care, noted:

Sleeping with your elbow straight is usually a gamechanger. There is something about keeping the elbow bent for long periods that irritates tennis elbow and makes the pain worse. It can be a bit challenging to figure out how to keep your elbow straight while tossing and turning in bed, but my patients who manage this report big improvements in their pain.

That endorsement piqued my interest. The Wikipedia article on tennis elbow also mentions this treatment clearly. With my nascent tennis elbow, I decided to try it for myself. Using a bowline knot (which does not slip), I tied a loop at one end of a bathrobe belt just big enough to wriggle my hand through, and a larger loop at the bottom to go around my thigh:

It is somewhat awkward to sleep with this on, but it is entirely bearable if you set your mind to it and plan ahead, e.g., where to position your nighttime tissue box. After only two nights on this protocol, I am now waking up with no pain in my elbow. Thanks, doc.

Steps To Grow Lettuce and Herbs in AeroGarden-Type Countertop Hydroponics Unit

This will be a longer-than-usual post, since I will try to include all the steps I used to grow salad ingredients in a compact (AeroGarden-type) hydroponics system. I hope this encourages readers to try this for themselves. See my previous post for an introduction to the hardware, including small modifications I made to it. I used a less-expensive ($45), reliable 18-hole MUGFA model here, but all the AeroGardens and its many knockoffs should work similarly.   Most plant roots need access to oxygen as well as to water; these hydroponic units allow the upper few inches of the root to sit in a (moist) “grow sponge” up out of the water to help with aerobic metabolism.

Step 1. Unbox the hydroponics unit, set up per instructions near a power outlet. Fill tank close to upper volume marking.

Step 2. Add nutrients to the water in the tank: usually there are two small plastic bottles, one with nutrient mix “A” and the other with nutrient mix “B”, initially as dry granules. Add water to the fill lines of each of these bottles with the granules, shake till dissolved. (You can’t mix the A and B solutions directly together without dilution, because some components would precipitate out as solids. So, you must add first one solution, then the other, to the large amount of water in the tank.)

There is more than one way to do this. I pulled the deck off the tank, used a large measuring cup to get water from my sink into the tank, a little below the full line. For say 5 liters of water, I add about 25 ml of nutrient Solution A, stir well, then add 25 ml of Solution B and stir. You could also keep the deck on, have the circulation pump running, and slowly pour the nutrient solutions in through the fill hole (frontmost center hole in the deck). You don’t have to be precise on amounts.

Step 3. Put the plastic baskets (sponge supports) in their holes in the deck, and put the conical porous planting sponges/plugs in the baskets. Let the sponges soak up water and swell. (This pre-wetting may not be necessary; it just worked for me).

Step 4. Plant the seeds: Each sponge has a narrow hole in its top. You need to get your seed down to the bottom of the hole. I pulled one moist sponge out at a time and propped it upright in a little holder on a table where I could work on it. I used the end of plastic bread tie to pick up seeds from a little plate and poke them down to the bottom of the hole. You have to make a judgment call how many seeds to plant in each hole. Lettuce seeds are large and pretty reliable, so I used two lettuce seeds for each lettuce sponge. Same for arugula (turns out that it was better to NOT pre-soak the arugula seeds, contrary to popular wisdom). If both seeds sprout, it’s OK to have two lettuce plants per hole, though you may not get much more production than from one plant per hole. For parsley*, where I wanted 2-3 plants per hole, I used three seeds each. For the tiny thyme seeds, I used about 5 seeds, figuring I could thin if they all came up. For cilantro, I used two pre-soaked seeds. I really wanted chives, but they are hard to sprout in these hydroponics units. I used five chive seeds each in two holes, but they never really sprouted, so I ended up planting something else in their holes.  

I chose all fairly low-growing plants, no basil or tomatoes. Larger plants such as micro-dwarf tomatoes can be grown in these hydroponics units; also basil, though need to aggressively keep cutting it back. It may be best to choose all low or all high plants for a given grow campaign. See this Reddit thread for more discussion of growing things in a MUGFA unit.

Once all the plugs are back in their holders, you stick a light-blocking sticker on top of each basket. Each sticker has a hole in the middle where the plants can grow up through, but they block most of the light from hitting the grow sponge, to prevent algae growth. Then pop a clear plastic seeding cover dome on top of each hole, and you are done. The cover domes keep the seeds extra moist for sprouting; remove the domes after sprouting.  Make sure the circulation pump is running and the grow lights are on (typically cycling on 16 hours/off 8 hours). This seems like a lot of work describing it here, but it goes fast once you have the rhythm. Once this setup stage is done, you can just sit back and let everything unfold, no muss, no fuss. Here is the seeded, covered state of affairs:

Picture: Seeds placed in grow sponges on Jan 14. Note green light-blocking stickers, and clear cover domes to keep seeds moist for germination. The overhead sunlamp has a lot of blue and red LEDs (which the plants use for photosynthesis), which gives all these photos a purple cast.

Jan 28 (Two weeks after planting): seedlings. Note some unused holes are covered, to keep light out of the nutrient solution in the tank. The center hole in front is used for refilling the tank.

Feb 6.  Showing roots of an arugula plant, 23 days after planting.

Step 5. Maintenance during 2-4 month grow cycle. Monitor water level via viewing port in front. Top up as needed. Add nutrients as you add water (approx. 5 ml of Solution A and 5 ml Solution B, per liter of added water). The water will not go down very fast during the first month, but once plants get established, water will likely be needed every 5-10 days. If you keep trimming outside leaves every several days, you can get away with having densely planted greens, whereas if you only harvest say every two weeks, the plants get so big they would crowd each other if you plant in every hole on the deck.

Optional: Supposedly it helps to keep the acidity (pH) of the nutrient solution in the range of 5.5-6.5. I think most users don’t bother checking this, since the nutrient solutions are buffered to try to keep pH in balance. Being a retired chemical engineer, I got this General Hydroponics kit for measuring and adjusting pH. On several occasions, the pH in the tank was about 6.5. That was probably perfectly fine, but I went ahead and added about 1/8 teaspoon of the pH lowering solution, to bring it down to about 6.0.   I also got a meter for measuring Electrical Conductivity/Total Dissolved Solids to monitor that parameter, but it was not necessary.

Feb 16: After a month, some greens are ready to snip the outer leaves. Lettuces (buttercrunch, red oak, romaine) on the right, herbs on the left.

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Feb 17: Harvesting a small salad or sandwich filler every 2-3 days now.

March 6: Full sized, regular small harvests. All the lettuces worked great, buttercrunch is especially soft and sweet. Arugula (from the mustard plant family) gave a spicy edge. Italian parsley and thyme added flavor. The cilantro was slower growing, and only gave a few sprigs total.

Closeup March 16 (three months), just before closing out the grow cycle. Arugula foreground, lettuce top and right, thyme on left, Italian parsley upper left corner.

Step 6. Close out grow cycle. At some point, typically 2-4 months, it is time to bring a grow cycle to a close. I suppose with something like dwarf tomatoes, you could keep going longer, though you might need to pull the deck up and trim the roots periodically.  In my case, after three months, the arugula and cilantro were starting to bolt, though the lettuce, thyme, and parsley were still going strong. As of mid-March, my focus turned to outside planting, so I harvested all the remaining crops on the MUGFA, turned off the power, and gently pulled the deck off the tank. The whole space under the deck was a tangled mass of roots. I used kitchen shears to cut roots loose, enough to pull all the grow sponges and baskets out. The sponges got discarded, and the baskets saved for next time. I peeled off and saved the round green light-blocking stickers for re-use. I cleared all the rootlets from the filter sponge on the pump inlet. Then I washed out the tank per instructions. It took maybe 45 minutes for all this clean-out, to leave the unit ready for a next round of growing.

Stay tuned for a future blog post on growing watercress, which went really well this past fall. Looking to the future: In Jan 2026 I plan to do a replant of this 18-hole (blocked down to 14-holes) MUGFA device, sowing less lettuce (since we buy that anyway) but more arugula/Italian parsley/thyme for nutritious flavorings. For replacement nutrients and grow sponges, I got a Haligo hydroponics kit like this (about $12).

Growing these salad/sandwich ingredients in the kitchen under a built-in sunlamp provided good cheer and a bit of healthy food during the dark winter months. The clean hydroponic setup removed concerns about insect pests or under/overwatering.  It was a hobby; at this toy scale it did not “save money”, though from these learnings I could probably rig a larger homemade hydroponics setup which might reduce grocery costs. This exercise led to fun conversations with visitors and children, and was a reminder that nearly everything we eat comes from water, nutrients, and light, directly or indirectly.  

*Pro tips on germinating parsley seeds – – Parsley seeds have a tough coating, and can take weeks to germinate. Some techniques to speed things up:

( 1 ) Lightly abrade the seeds by gently rubbing between sheets of sandpaper.

( 2 ) Soak in warmish water for 24-48 hours.

( 3 ) For older seeds, cold stratification (1–2 weeks in a damp paper towel in the fridge) may help break dormancy.

Is the Silver Bubble Bursting?

This is a five-year chart of the silver ETF SLV:

By most standards, this pattern looks like we entered a bubble a few months ago: speculative froth, unjustified by fundamentals. Economic history is replete with such madness of crowds. It is accepted wisdom on The Street that these parabolic price rises seldom end well. I lost a few pesos buying into the great gold bubble of 2011. All sorts of justifications were given at the time by the gold bugs on why gold prices ought to just keep on rising, or at least reach a “permanently high plateau” (in the famous words of Irving Fisher, just before the 1929 crash). Well, gold then proceeded to go down and down and down, losing some 60% of its value, until the price in 2015 matched the price in 2009, before the great bubble of 2010-2011.

Today, similar justifications are proffered as to why silver is going to the moon. There is a long-standing deficit in supply vs. demand; it takes ten years for a new silver mine to get productive; China has started restricting exports; Samsung announced a breakthrough lithium battery that can charge in six minutes, but requires a kilogram of silver; AI infrastructure is eating all the silver. These narratives seem to feed on each other. As the silver price moved higher in the past month, out came yet wilder stories that ricochet around the internet at high speeds: the commodities exchanges have run out of physical silver to back the paper trades; and the persistent claim that “they” (shadowy paper traders, central banks, commodity exchanges, the deep state, etc.) are “suppressing” silver and gold prices by means of shorting (which makes no sense). Given this popular shorting myth, it was with great glee that the blogosphere breathlessly spread the bogus story that some “systematically important bank” was in the process of being liquidated because it got squeezed on its silver short position.

The extreme price action at the very end of December (discussed below) was like rocket fuel for these rumors. Having bought a little SLV myself so as to not feel like a fool if the silver rally did have legs, I spent a number of hours as 2025 turned to 2026 trying to sort all this out. Here are some findings.

First, as to  the medium term supply/demand issues, I refer the reader to a recent article on Seeking Alpha by James Foord. He shows a chart showing that silver demand is increasing, but slowly:

He also notes that as silver price increases, there is motivation for more recycling and substitution, to compensate. He concludes that the current price surge is not driven by fundamentals, but by paper speculation.

The last ten days or so have been a wild ride, which merits some explanation. Here is the last 30 days of SLV price action:

Silver prices were rising rapidly throughout the month, but then really popped during Christmas week, reaching a crescendo on Friday, Dec 26 (blue arrow), amid rumors of physical shortages on the Shanghai exchange. To cool the speculative mania, the COMEX abruptly raised the margin requirements on silver contracts by some 30%,  from $25,000 to $32,500, effective Monday, Dec 29. I think the exchange was trying to ensure that speculators could make good on their commitment, and the raise in margin requirement would help do that. (Note, the exchange is liable if some market participant fails to deliver as promised and goes BK).

Anyway, this move forced long speculators to either post more collatoral or to liquidate their positions, on short notice. Blam, the price of silver dropped a near record amount in one day (red arrow). For me, a little minnow caught in the middle of all this shark tank action, the key part is what came after this forced decline. Was the bubble punctured for good? Should I hold or fold?

As shown above, the price has traded in a range for the past week, with violent daily moves. Zooming out to the a one-year view, it looks like the upward momentum has been halted for the moment, but it is unclear to me whether the bubble will deflate or continue for a while:

I sold about a quarter of my (small) SLV holding, hoping to buy back cheaper sometime in the coming year. Time will tell if that was a good move.

Usual disclaimer: Nothing here is advice to buy or sell any security.

P.S. Tuesday, Jan 6, 2025, after market close: I wrote this last night (Monday, Jan. 5) when silver was still rangebound. SLV was about $69, and spot silver about $76/oz. But silver ripped higher overnight, and kept going during the day, up nearly 7% at the close to new all time high. It looks like the bubble is alive and well, for now. Congrats to silver longs…