AI markets have flipped traditional asymmetry, with rallies of 20% more now common, even in large‑cap names that historically moved far less.

Short interest, once a bearish signal, now fuels squeezes and momentum that push speculative stocks higher and turn short sentiment bullish.

Traders going short should weight positions by beta or volatility, avoid crowded shorts, use puts or spreads for short exposure, and buy calls.

A well-documented principle in equity markets is the asymmetry between upward and downward price movements. Whether measured in dollars or percentages, declines of 5%, 10%, or 15% occur more frequently than equivalent rallies, underscoring the market’s natural downside bias.

In the options market, puts that are equally out-of-the-money as calls tend to be more expensive, reflecting downside risk. This difference in implied volatility is known as “skew.”

SPX 90 – 110 Put Skew

Why Asymmetry Exists

Most investors are long. Herd behavior can trigger cascades of selling, while rising stocks often meet profit-taking that caps momentum.

News flow is asymmetrical: disasters, crises, and scandals dominate headlines, while good news is incremental.

The leverage effect amplifies volatility as assets decline. Equity equals assets minus liabilities; as assets fall, leverage rises, increasing volatility risk.

Historical narratives emphasize crashes and bear markets as defining events.

Other asset classes differ: commodities like oil often show positive skew, with sharp spikes triggered by single events.

Bubble-Driven Market Dynamics

In AI-driven markets, this pattern is reversed. Large-cap stocks like AMD and Nokia have surged 20% in a single day on AI-related news. Previously, AMD’s largest one-day gain over five years was around 11%. For Nokia, the next highest gains were 15% and 10%.

This shift has major implications for options trading. Traders must now consider the possibility of a 20% rally, which could cause deep out-of-the-money calls to jump from $0.00 or $0.01 to meaningful prices. Call sellers face similar risks as short sellers—the stock could surge unexpectedly.

There’s also longer-term upside risk in AI and adjacent sectors like quantum computing and battery technology. These areas have delivered returns in the hundreds of percent. The risk in selling calls or shorting stock is not only theoretically unlimited—it can be practically unlimited. The risk is clearly to the upside.

Such returns for large-cap companies are theoretically improbable based on option pricing models that account for all scenarios. And it’s not just a one-off—it’s a pattern.

If and when the bubble bursts, short positions and short calls could be highly profitable—but timing remains uncertain.

Guidelines for Shorting in an AI-Driven Market

Dismiss the idea of equal notional exposure. Instead, weight stocks by beta or volatility—allocate less to higher-beta names.

Historically, heavy short interest was seen as a bearish signal. But in today’s market, the most shorted basket is up significantly. Heavy shorting is bullish—not in sentiment, but in outcome.

Shorts are targeting stocks with weak fundamentals, yet speculative names are outperforming. Many AI stocks show high short interest, are crowded, and continue to rise.

Rising stocks are triggering numerous short squeezes—some appear to be in a perpetual squeeze. This is another dynamic where shorting pressure turns bullish.

Avoid shorting heavily shorted stocks unless conviction is extremely high. Consider targeting less-shorted names.

Maintain a net long bias while the AI frenzy persists.

Use puts to express bearish views—limiting upside risk while maintaining short exposure. Costs can be reduced via put spreads.

Avoid shorting stocks that have call skews exceed put skews, which indicate investors see extreme upside.

Instead of going long with large downside risk, buy calls to benefit from sharp upward moves.

Consider shorting ETFs, which tend to be less volatile. For example, AIQ.

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