Decoding Jargon Monoxide: Simplifying Complexities in Option-Based ETFs and Derivatives

Last week, I was part of a panel conversation about option-based exchange-traded funds (ETFs). The audience included a variety of advisors and ETF issuers. I’ve written about the growth in this area of the market in the past. Cliff notes: it’s growing by leaps and bounds.

After the discussion, someone came up and asked if I was a professor, ostensibly because of how I tried to break down some of the complexities that can push people away from derivative-wrapped products. My approach eschews much of the parochial language the industry leans into. Along those lines, I am reminded of a term an old friend (thank you Liz Gerber) introduced to me a few years back: “jargon monoxide.”

She came to understand the phrase from her Stanford PhD advisor, Bob Sutton. The concept is fascinating, and the practice is pervasive. Here’s a question from Business Strategy on this topic:

What is a common source of friction that you’ve seen across most organizations?
SUTTON: One of the things that I’ve been obsessed with for years is the notion of “jargon monoxide”—that is, people in organizations often use language that, well, means nothing. It’s sort of BS. It’s so complicated nobody can understand what they’re talking about. And people use different languages in different silos. That undermines communication—both with clients and across the organization.

Derivatives Implications

Derivative users, particularly on the institutional side, are as prone to jargon monoxide. Part of my work, whether it’s written, spoken or otherwise, is to explain the jargon in approachable terms.

Ultimately, people don’t do things they don’t understand. You may sound somewhat intelligent throwing around jargon at a dinner party, but people won’t be persuaded if your language isn’t understandable.

Self-directed traders continue to become more sophisticated, but a handful of topics are still likely to fall beyond the pale for most individual traders.

That in mind, I’ve been thinking about correlation in the markets as well as the proliferation of artificial intelligence (AI). Let’s combine the two and cut through some jargon.

ChatGPT prompt: What does equity index realized correlation mean?

Response: Equity index realized correlation is a statistical measure of how closely the returns of the individual stocks within an index move together, based on actual historical data over a given period.

Here’s the breakdown:

Correlation measures the degree to which two assets’ returns move together.

• A correlation of +1 means they always move in the same direction.
• A correlation of 0 means they move independently.
• A correlation of -1 means they always move in opposite directions.

The output includes a conceptual formula comparing the volatility of constituent stocks to the volatility of the index.

Source: ChatGPT

Why It Matters (according to ChatGPT):

Investors and traders use it to understand the diversification benefits within an index.

• A low realized correlation means diversification is effective (stocks are behaving differently).
• A high realized correlation means diversification benefit is reduced since everything moves together.

My take: Correlation describes the extent to which two or more variables move in unison with one another. This term can be applied to an index, like the Nasdaq-100® (NDX). There are 101 (Alphabet has two share classes) securities in the index. Sometimes, the group moves in relative lockstep (think: West Point Cadets). Other times, the stocks that make up the index are dancing to their own beat (think: group of kindergarteners told to explore).

At present, NDX® constituents are exhibiting unusually low correlation. Here’s a chart that plots the realized correlation (RC) for NDX® stocks over the past five years. Like other “volatility” measures, your lookback window matters. The white line shows RC on a 1-month basis. The teal line shows it on a 3-month basis.

Source: Bloomberg

Looking at the 3-month measure, the only comparable periods were June 2025 and August 2021. The current measure is below the lows from 2017 (lowest volatility year for the NDX® ever).

Cliff notes: At present, the NDX® exhibits a significant amount of idiosyncratic (stock specific) risk and very little systematic (index wide) risk. In cleaner terms, it’s been a stock pickers market since the early April tariff escalation fears subsided.

Now, let’s introduce the options component, which is always forward-looking. Most index option users are aware of the relationship between historical volatility and implied volatility. Put simply, the degree to which the index has vacillated recently often informs the expected swings in the future.

There’s a similar dynamic between realized and implied correlation. Generally, when the index exhibits low levels of realized correlation, the option market anticipates it will likely continue. There are certainly exceptions, but the dynamic tends to be true.

It’s important to point out that realized correlation often declines during the earnings season. That was the case during the Q2 reporting period.

Practically Speaking…

So, how does all this matter to you?

The answer is, like so many things, it depends.

For stock pickers, the backdrop has been favorable for months. Hopefully you’ve had outsized allocations to NDX® constituents, like AppLovin, Micron, Broadcom and Palantir. Those securities have gained between 175% (APP) and 130% (PLTR) since the market closed on April 4^th (tariffs).

In a perfect world, you would have avoided the declines in stocks like Lululemon, Charter Communications and Keurig Dr Pepper. They have slid between 35% (LULU) and 20.3% (KDP) over the same time frame.

The thing is, we live in an imperfect world. We’re tasked with making consequential decisions with imperfect information all the time. Most investors are well served by indexing their equity exposure. Between the April 4^th close and September 16^th, the NDX® has advanced by nearly 40%. By comparison, the S&P 500® Index gained just over 30%.

Source: YCharts

Very similar dynamics play out if you choose other inflection points for equities. The outperformance since the “bottom” of the pandemic selloff reflects the broader point.

Source: YCharts

Let’s put it in more concrete terms. $10k invested in an NDX® tracking vehicle in mid-March 2020 is now worth nearly $34k. $10k invested in an S&P 500® tracker on the same day would be worth $28.39k five and a half years later. That’s a $5.48k difference on a $10k investment.

The Choice is Yours

Bringing it back to correlation, the average 30-day correlation between the NDX® and the S&P 500® since the COVID lows is 0.918. The highest correlation possible is +1.0. The measures have been ~92% correlated (30-day windows) over the past 5 ½ years. However, there has been a very meaningful outperformance on the part of one equity measure.

We make decisions every day that are far less consequential than those influencing our financial well-being. Some are informed by data; others are more qualitative. Think about where your marginal investment dollars flow and expect that if, and when, correlations increase, it’s very likely both indexes will fall.

In that case, you’ve got Nasdaq-100 Index Options (NDX®) to potentially buffer the account.

No jargon necessary. Keep coming back.