Moontower #319

In this issue:

• free lunches and non-tradeoffs
• VIX and buy signals
• delta-hedged risk reversals

Friends,

As one of my favorite HS teachers used to say, every silver lining has a cloud. (That this is one of my favorite teachers, you could probably predict my teenage affection level for rainbows and pop music). It seems I was destined to take to the idea of no free lunch easily.

Costs and Benefits

Trader and author Brent Donnelly, like most of us, struggles with the drawbacks of the otherwise transformative tech packed into our smartphones.

I Want It, But I Don’t Like It | 8 min read

The shocking and amazing thing about the unprecedented economic success of surveillance capitalism is how easily many of us (including me) surrendered to the extraction layer without much of a thought or a fight.

It’s a great example of what DFW called our default groove or “water”. That he’d spend the commencement speech warning us about lapsing into zombie mode BEFORE the smartphone was even invented indicates just how hard it really would be to overcome infinite scroll.

The short book I most commonly recommend to people is Neil Postman’s lengthy essay Amusing Ourselves To Death (my notes). It was published in 1985. My edition as a prophetic foreword:

Brent offers his Easy, Medium, Hard interventions to combat his phone. I share the struggles and have had with various levels of success tried many of these myself.

While the article is ultimately practical, I appreciated Brent’s abstract observation that the phone has both an extraction layer designed to monetize your attention as well as an agnostic technological utility layer (phone, camera, processing). His strategy is to minimize the former while maintaining the benefits of the latter. In other words, this is not the realm of a tradeoff.

In The Sydney Opera House Exam Question Dan Davies writes:

You are almost certainly not at the efficient frontier of managing your phone’s costs and benefits.

So there must be a free lunch after all. Check out Brent’s interventions.

Accelerated upskilling

Wednesday’s oh well included some links about learning and upskilling. Here’s another one I’ve come across since:

How to ‘git gud’ at Games (Faster Than Everyone Else) | 4 min read

This is from SIG’s gaming blog.

“One of the least efficient ways to improve at a game is simply playing it.”

In our latest gaming blog, Adam, a competitive gamer who has reached Master rank with all races in StarCraft II, cracked the top 50 in North America in Hearthstone Battlegrounds, and is currently ranked #1 in the world in Patchwork on BGA, looks at how you can “git gud” at games (faster than everyone else, of course).

It offers 5 tips to accelerate learning. Actually, “tips” is a flaccid description of Adam’s suggestions. They are the difference between the preparation of amateurs and pros in any skill-based activity. It’s more like an advantage loop. Combining it with talent (which is why matching your activities to your abilities is so important) and persistence is a very simple recipe to achieving rare outcomes.

I didn’t say easy. Just simple.

Maxen-Art

This past weekend I stood up a website for 10-year old to host his art. In the age of AI this is easy even without a website builder.

I bought the domain name on Namecheap, Max found gallery sites he liked that were minimalist, and I told Claude to mimic the format. The HTML is produced is hosted on Github along with a folder where we upload his images. Vercel is the host serving the webpage. There is an automatic webhook from Git to Vercel so that anytime Git updates, Vercel updates the page.

🔗maxen-art.com

 

Money Angle

Here’s Victor Haghani:

A high VIX1 is widely considered to be one of the cleaner buy signals out there. A recent piece in The Financial Times made the case directly: when the VIX climbs above 30, forward returns have been well above average, positive most of the time, with double-digit six-month gains.

The Financial Times case is “buy the f’n dip” logic with a VIX gate. It’s exactly the type of thing that a layreader numbly nods at when the SPX is sitting near an all-time high. The Financial Times’ case is lazy from the perspective of both investors and active traders. For the investor, it’s just survivorship bias. Knowing what we know now every pullback has just presented a bargain. The market literally “going on sale” like it’s Prime day. VIX spikes over 30 just coincide with the sales.

The question you care about is one that an active trader hearing that statement would think to hypothesis test. Given that buying any time before an all-time-high has been worked out well, how do I distinguish between relatively better or worse buys?

Back to Victor:

What that leaves out is risk. Buying the spike means taking on a lot more of it, and the strategies that did the opposite, trimming exposure when fear ran high, held up better. So the popular signal may have it backwards.

Raw returns aren’t the right thing to optimize. You care about compounded returns since investing is a repeated game. Compounded returns are risk-adjusted returns because a geometric growth process penalizes volatility.

Elm Wealth tests FT’s claim not on raw return but Sharpe Ratio, or how much return you’re getting per unit of risk taken, as the variable to maximize if we care about risk-adjusted returns.

When Fear Spikes, Should You Buy? Elm Wealth | 5 min read

What they found when they ran the numbers on S&P 500 and VIX data from 1990–2026, they found:

• A plain static stock/T-bill portfolio: Sharpe ratio of 0.50
• A strategy that buys more when VIX > 30% (the popular advice): 0.47 which is slightly worse than the null case
• A strategy that reduces exposure when VIX is high (inverse sizing): 0.54
• A simple momentum strategy (cut exposure when the market is falling, which is typically when VIX is elevated): 0.59 — the best performer

It’s always bears repeating how risk scales:

When volatility doubles, the risk of holding stocks is actually four times as large (because variance, not standard deviation, is what matters to risk).

To merely hold your position when VIX doubles, expected returns would need to quadruple. To justify doubling down, they’d need to increase eightfold, which the authors deem practically implausible.

This post led to some smart quants chiming in on X.

Here’s @ptuomov:

This is a very low-resolution statement because each word represents many variable choices when you get into research:

Define “high”, define “trending”, “six months” was probably just a placeholder term

The degrees of freedom on the choice notwithstanding, the idea makes sense:

You are using the signals from the derivatives market, a place where leverage attracts early movers and smart money, to give a leading indicator on “the market environment is changing from the status quo” and collective anchoring biases make the wider market underreact. The way to profit from the seeds of this new information is to follow the trend.

There’s that line what the wise man does in the beginning, the fool does in the end.

The quant view is trying to find the signal of moving from the end of one cycle to the beginning of another. Trend following in a sense has a long option flavor. The premium is all the false starts and the payoff is when you finally catch a trend.

Meanwhile, buying the dip is a short option strategy in that it is betting on mean reversion as opposed to further divergence. Buying stock when VIX spikes is a mean reversion trade. But when you examine that as a strategy from the vantage point of all-time highs, it takes for granted that the mean is a good thing.

When you read a claim about a course of action, it’s good mental hygiene to first triage it as: is this directionally long or short vol?

Money Angle For Masochists

We recently added multi-leg support to our Attribution Visualizer, our tool for allowing you to track an option contract’s p/l assuming you hedged the delta daily. The tool breaks out the p/l according to gamma + theta (which sum to realized p/l) and to implied vol (vega p/l).

With multi-leg support, you can now entertain yourself with countless questions. Like “how would a masochistic skew trade work out if I trade a risk reversal and hedge daily?”

I ran a few risk reversals through the attribution tool.

USO: Buy call/sell put after the Iran war started

Date: March 13

Expiry: June 18, 2026 (~ 3 months)

Spot: $119.92

Risk reversal: 140c / 100p (equidistant strikes ~ each 17% OTM)

Initial hedge: Short 73 shares per risk reversal (the RR had .73 delta)

The war had already flipped the skew hard toward upside strikes. The $140 call traded 94% vol against the $100 put’s 83% IV. It cost $5.83 in option premium.

At expiration, the stock expired at $114.87

So how did it work out to buy the premium IV?

Not good. The cumulative delta-hedged p/l was a loss of over $4.50 as you lost to both realized vol and vega. At the initiation of the trade, paying the premium vol meant you were flattish gamma but paying theta.

You were also long vega because, despite the options being equidistant, at a generally elevated vol level the lognormality of the underlying distribution and its associated positive skew pumps up the delta of calls. In fact, the 140 call was ~.47 while the 100 put, which is closer in dollar space, was only .27d. The higher call delta says the 140 strike is much “closer in vol space”. That’s why the equidistant risk reversal cost so much premium to buy the call. You are buying at OTM that has a delta that we usually associate with near ATM options!

Let’s adjust the strikes so that our call and put are both ~.25d

To equalize deltas against the $100 put you have to buy…drum roll please…

The $190 call! 58% OTM for 101% IV. Now you collect a $2.17 credit to own the call and short the 100 put. Your initial Greeks mostly vanish.

The trade still loses, but it fares much better as the loss is only $1.29.

It’s tempting to conclude paying a premium vol doesn’t work. But if you bought the much cheaper call and shorted the put on a hedged riskie in SPY before the war started, then you got smoked if you chose April 30th expiry (SPY bottomed the last day of Q1), recovered once the market started rallying, only to lose again as the market…continued rallying! SPY riskie:

I’ve said it repeatedly over the years in different ways, but riskies are the whips and leather of the option world. If you bought the call on the SPY Feb 720/650 risk reversal on the first trading day of the year and hedged daily until expiration, you actually would have lost $.25 despite the following:

• the trade collected about $2.75 in premium at the outset
• the stock’s closing prices stayed inside the range of $675-$700
• the call you bought was 10.2% IV and the put you sold was 16.8% IV

In Financial Hacking, Philip Maymin invents an optimistic junior trading assistant who sits down his bosses at the bank to explain that he has found an infinite money machine. Selling the high IVs in SPY puts and buying the cheap IV in SPY calls. Maymin asks the reader to figure out why this logic doesn’t work.

Our tool provides the day-by-day audit which feeds the charts. Armed with that, Claude does an admirable job of not only answering Maymin’s prompt to the reader but also pinpointing exactly which days carry the biggest weight in the answer.

I’m excited about the tool even though using it feels like performing surgery on myself. Which weirdly reminds me, I have an option trivia question for readers who made it this far:

Stay groovy

☮️

Moontower Weekly Recap

• oh well
• war only happens at night