Cboe Global Markets

Inside Volatility Trading: Market Knowledge

Kevin Davitt
▬
February 9, 2021

I had a secret meeting in the basement of my brain

It went the dull and wicked ordinary way

-Secret Meeting - The National

The Curse of Knowledge

In the late 1980s, a group of economists working off Baruch Fischhoff’s research into hindsight bias coined the phrase “the curse of knowledge.” They set out to test whether information asymmetries yielded better decisions. While knowledge is power, in many circumstances that’s less than half the story. Our ability to impart our insight is often impaired.

A year later, Elizabeth Newton, a Stanford graduate student depicted “the curse of knowledge” thesis by asking groups of students to “tap out” memorable songs with their fingers while others listened and attempted to guess the tune. The assumption on the part of the “tappers” was that the listeners would quickly recognize common jingles like “Happy Birthday.” Newton asked the “tappers” to predict how many of the 120 songs on the list the listeners would recognize based on their rhythm. The forecast, prior to tapping, was for a 50% success rate.

What do you think the actual success rate turned out to be?

  • 75%
  • 25%
  • 10%

Well, only three songs were accurately identified for a success rate of 2.5%. Try it at home…I imagine you’ll be surprised, or frustrated, or both.

The experiment showcases information asymmetry: one party knows the tune they’re tapping and the other has no knowledge; the “information” sits firmly with one party. Despite the likelihood that experiment participants were well-versed (pun intended) with a song like Happy Birthday, it was (and remains) profoundly difficult to relay the necessary message. The tappers, unable to put themselves in the listeners situation, experience their knowledge cursing them.

These types of experiments have played out across industries, classrooms, and homes for centuries. Perhaps it’s being played out in the capital markets right now.

Market Knowledge

Consider the business model of a long/short hedge fund. The underlying thesis involves identifying and understanding the correlation of assets. For example, we identify a pair of businesses in the same industry and choose to allocate capital, “go long,” to the relatively cheap business and simultaneously sell, or “short,” the less attractive business. It’s a relative value play that’s typically considered low(er) risk when compared to an outright long or short.

This type of trading occurs in the options (volatility) markets as well. It’s often referred to as dispersion trading. The basic approach involves either buying or selling index options and conversely selling or buying options on the individual constituents in the index.

Pairs trading, dispersion trading and other sophisticated strategies that have been employed effectively for many years are typically considered lower risk ways to potentially generate alpha. The individuals and firms employing these approaches often wield an impressive toolkit for making trading decisions: education, capital, information (in the form of data sets and back-testing), and rigorous risk parameters.

But what happens in situations where “knowledge” doesn’t matter?

What happens when markets don’t behave like the data leads us to believe they ought to?

Source: Twitter, @WayneHimelsein

Reality is Messy

In late January, GameStop (GME), which began 2021 with a market cap of roughly $1.2 billion, was briefly worth about $33 billion. GME has shown losses of ~$500 million/annum for the past three years. Their business model was considered outdated and many sophisticated market participants tried to exploit their decline by remaining short GME shares.

For some context, BestBuy (BBY) has a market cap of $30 billion. Over the past decade they have staved off obsolescence by executing on a turnaround plan. BBY partnered with Amazon to become the exclusive retailer for some products (Fire Smart TV). They have similar agreements with Apple, Microsoft, Samsung, and other leading electronic makers. They shuddered underperforming stores and embraced efficiency. BBY has shown positive earnings of roughly $4.3 billion over the past three years.

A hedge fund might trade GME and BBY in a pairs/relative value strategy. They would likely own BBY long and be short GME. Here’s the wrinkle: one leg of that hypothetical strategy became (in hindsight) “crowded,” exploited by a wide variety of price insensitive market participants with ostensibly far less fundamental “knowledge.”

Float

In capital markets, the term “float” speaks to the availability of shares issued by a company in the secondary market. The figure is calculated by subtracting any restricted shares (held by insiders/locked-up) from the company’s outstanding shares. Options trading does not impact float availability. Float is a function of issuance on the part of the securities’ underwriters and the number of restricted shares.

As of 12/31/2020, GameStop had the highest short interest level as a percent of float in the Russell 3000. It ended last year with 261% of float shares short. At the same point in time, the next most shorted equity was Ligand Pharmaceuticals (LGND) with a percent of float short reading of 106%. The tenth most shorted name was National Beverage Corp (FIZZ). 63% of their floated shares were short.

Here are some additional data points for context, short interest as a percentage of float:

  • Apple and Microsoft are around 2%. 
  • Amazon is less than 1%.

“The rearview mirror is always clearer than the windshield”

Russell 3000: Stocks with Highest Short Interest as a Percent of Float

Source: YCharts, Charlie Bilello

Short sellers play an integral role in the ecosystem. Markets are tools for price discovery, which are dependent upon willing buyers and sellers. According to research, short sellers, with their unique perspective and risk tolerances, may predict negative earnings surprises or other disruptive news. Going back nearly twenty years, short sellers helped illuminate the financial chicanery at Enron that led to their demise.

If interested in learning more, NPR put out a succinct piece explaining short selling last month.

Craig Lazzara of S&P Dow Jones also penned an insightful piece on the recent “short squeeze” dynamics.

Crowded Rooms & Small Doors

Indoor spaces have capacity signs for a reason. Using a contemporaneous example, restaurants in many areas of the country now have limitations on the number of people who can be seated and the required square footage to accommodate social distancing to help stem the spread of COVID-19.

Think about a concert hall or sporting venue. Madison Square Garden has a capacity of just under 21k for basketball and hockey games. More bodies than that would violate a fire code and the building would be considered unsafe.

While the analogy isn’t perfect, there are no explicit capacity limitations in capital markets. Events like we’ve observed in recent weeks in stocks like GME, BBBY, AMC and others point to capacity vulnerability. What if 54,810 (261% of capacity) people attended an event at Madison Square Garden? There’s a very real possibility of a stampede if a number of people needed to exit quickly.

Dispersion Trading

We’re coming to the end of earnings season. The number of companies beating The Street’s expectations (86% as of early Feb) on an EPS basis is well ahead of recent quarters. As mentioned earlier, sophisticated market participants, including liquidity providers, dealers (banks), and hedge funds might employ a dispersion trading strategy either passively or opportunistically.

Dispersion trading looks to profit from price/vol differences between index options and, typically, options on the largest equities within the index. Somewhat akin to pairs trading in the equity world, it’s a thesis based on historical relationships. The index options marketplace has demonstrated greater capacity than many single name equities. Average daily volume in SPX options in 2020 was ~1.25M.

Earnings season typically gives rise to greater market dispersion as volatility in specific equities (and the related options) picks up, but index volatility tends to remain muted. Positive news from one S&P 500 constituent may mute the impact of negative news from another.

One hypothetical dispersion trading approach might involve selling ATM index option straddles (strangles) to buy straddles (strangles) on the top index components on an appropriately weighted basis. If executed when the implied correlations are unusually high, the thesis posits that index option volatility was rich, or overpriced, relative to a basket of constituent equity option volatility. In theory the approach is delta neutral, or directionally agnostic, and adjusted to capitalize on volatility discrepancies as opposed to directional changes.

Cboe tracks and publishes an index designed to track the correlation between IVs for the top fifty index option constituents (weighted) and the IVs of the index itself. The Implied Correlation Indices have one-year and two-year maturities.

During volatile periods like March 2020 or Fall 2008, correlations typically increase. There’s a “baby out with the bathwater” mentality. Contagion occurs as fundamentals take a back seat to more primitive survival concerns. During more “normal” stretches, correlations tend to weaken. The recent events characterized by wild swings in many small-cap companies drove dispersion measures for small-cap indices to record levels. The YOLO crowd seemingly subscribes to the Diversification be Damned mindset.

S&P Small Cap 600® — One Month Index Dispersion

Source: S&P Dow Jones Indices. Data as of month end January 2021. Provided for illustrative purposes only. 

According to S&P Dow Jones data, if you excluded the impact of GameStop in late January, the monthly dispersion reading would have measured 58%. Including GME drove that calculation just beyond 200%.

Knowing What We Don’t Know

In the previous Inside Volatility, I referenced a point early in my career (trading options on the Cboe floor) where I was asked whether I wanted to be right or to make money. To this day I continue to grapple with the desire for both, but I’ve become more resilient as a result of recognizing how much I don’t know. Respecting the limitations of our knowledge as well as our ability to convey what we believe we know is a skill. One I’m still working on. Lucky me!

“We construct an expected world because we can’t handle the complexity of the present one, and then process the information that fits the expected world and find reasons to exclude the information that might contradict it.” – Charles Perrow

You could’ve made a safer bet

But what you break is what you get

You wake up in the bed you make

I think you made a big mistake

Lucky You – The National

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