Short Squeezes: A Four-Factor Model
Anticipating and riding short squeezes has grown in popularity as an investment tactic in recent years. The GameStop short squeeze, galvanized by motivated retail investors on internet message boards, is a vivid example of this phenomenon.
The ideal outcome for a prospective short-squeezer is what we’ll call the short-squeeze trifecta: They must identify the short squeeze before it happens, successfully ride the stock as its value soars on the way up, and bail out before the price falls back down to earth.
Stocks that end up in a short squeeze tend to exhibit two well-known determinants: They have high short interest and are thinly traded. But do other factors come into play? We wondered whether certain macro conditions might correlate with greater numbers of short squeezes or if short squeezes were more common in particular sectors.
Our analysis indicates two additional factors are associated with increased short squeeze activity: elevated market uncertainty and speculative technologies with yet-to-be-determined long-term value.
Strict and Loose Short Squeezes
To study short squeezes over time, we first had to develop a methodology to establish whether they actually took place. Using data from all publicly listed US companies from 1972 to 2022, we defined two distinct categories of short squeezes: “strict” and “loose.” A strict short squeeze is when a stock’s price rises by 50% to 500% and then falls back down to between 80% and 120% of its previous value in the course of one month. The same pattern occurs in a loose squeeze but over two months.
This approach identified 1,051 strict short squeezes and 5,969 loose short squeezes during the study period. The results for strict short squeezes are presented below. The loose method demonstrated qualitatively similar results.
Strict Short Squeezes by Year
The number of strict short squeezes varied considerably over time. Many years had close to zero while others had more than 100. The five most active short squeeze months, normalized by the total number of contemporary equity listings, were February 2021, May 2020, October 2008, February 2000, and October 1974.
What do all these months have in common? They fell amid periods of extreme market uncertainty. Inflation and COVID-19 infections were resurgent in February 2021, for example. In May 2020, the pandemic had upended life as we know it. The global financial crisis (GFC) and the associated panic were in full swing in October 2008. In February 2000, the dot-com bubble was approaching its speculative peak before beginning its subsequent downward spiral. High inflation, oil price shocks, and a severe recession were all center stage in October 1974, and the US Federal Reserve would soon start slashing interest rates, prioritizing economic growth over reducing inflation. So tough times for the markets and the larger economy tend to be good times for short squeezes.
How did strict short squeezes vary by sector? They occurred most often in biotech, with 20 in 2000 and 23 in 2020. These were the top years for short squeezes for any sector. Software and computing was the second most common short-squeezed sector.
Strict Short Squeezes by Sector
The biotech and software and computing sectors share a heavy reliance on new and often unproven technology. This makes them more prone to speculation, more difficult to value, and, as our data show, likelier targets for short squeezes.
By contrast, the least short-squeezed sectors are railroads, lodging, life insurance. These all have established, well understood business models and little uncertainty around their valuations. They have little appeal for potential short-squeezers.
So to determine whether a stock might become the target of a short squeeze, there are four criteria to keep in mind: Is the stock being shorted? Is it thinly traded? Does it rely on unproven technology? Are macro conditions especially unstable?
To be sure, short squeezes are not especially common phenomena, so even if all four conditions apply, the odds of predicting one are still very long. And as GameStop demonstrates, there are always outliers. Moreover, even if these four factors help identify short squeezes before they happen, their trajectories — how quickly they crest and crash — will always be fraught and uncertain. Which is why short squeezes are waves we shouldn’t stake too much on catching and riding.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
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1 thought on “Short Squeezes: A Four-Factor Model”
A timely, useful, insightful and beautifully written article. Worth everyone’s time to read this.