Reuters: AI Hyperscalers Upend the Usual Earnings Stock-Swing Pattern

ORATS data shows first-week earnings straddles gained 23% on average as AI giants flipped the usual earnings-season volatility pattern.

Summary

ORATS data featured by Reuters shows an unusual earnings-season reversal: first-week long straddles gained 23% on average, versus a 2% average loss over the previous 12 quarters, as major AI and hyperscaler stocks produced outsized post-earnings moves.

August 11, 2026

ORATS data featured by Reuters shows an unusual reversal in this earnings season: some of the market’s largest AI and hyperscaler stocks produced bigger post-earnings moves than the smaller companies that typically dominate earnings volatility later in the season.

Reuters’ Saqib Iqbal Ahmed reported that the first week of second-quarter earnings produced unusually strong results for options straddle buyers, according to ORATS data.

The difference from recent history was substantial.

For companies reporting during the first week of earnings season, long straddles generated an average 23% gain. Over the previous 12 quarters, the comparable first-week strategy had produced an average 2% loss.

By the fourth week, the pattern had reversed. Straddles produced an average 6% loss, close to the historical fourth-week average loss of 5%.

ORATS Earnings Season Report for August 10, 2026, comparing current earnings moves and implied moves with historical averages.

An Unusual Earnings Season

Normally, earnings season begins with many of the market’s largest and most heavily followed companies before shifting toward smaller companies in later weeks.

Smaller companies often experience larger earnings reactions because they tend to have thinner liquidity, smaller floats, less institutional ownership, and less analyst coverage.

This quarter has looked different.

Major AI and hyperscaler companies including Amazon, Microsoft, Alphabet, and Meta produced substantial post-earnings moves as investors reacted to whether enormous AI capital expenditures appeared to be translating into results.

As ORATS founder Matt Amberson told Reuters:

“The smaller companies in recent weeks have had more muted earnings moves – a contrast to the early weeks when AI and hyperscalers' reports helped drive larger-than-usual moves.”

What the Options Data Shows

The profitability of a long earnings straddle depends on the magnitude of the underlying stock move relative to what the options market priced before the announcement.

This earnings season, the largest companies reporting early generated enough movement to make that trade unusually profitable on average.

Week 1: +23% average straddle return

Historical Week 1: -2% average over the previous 12 quarters

By Week 4, the advantage had disappeared:

Week 4: -6% average straddle return

Historical Week 4: -5% average

Instead of earnings volatility building as the season moved toward smaller companies, much of the exceptional movement arrived early with the AI giants.

For options traders, it is another example of why historical tendencies are useful benchmarks rather than fixed rules. Earnings behavior can change when a powerful market theme concentrates investor attention, capital, and uncertainty in a relatively small group of companies.

ORATS provides historical options data, volatility analytics, scanners, and backtesting tools designed to help traders study those changes rather than assume yesterday’s pattern will repeat tomorrow.

Read the Reuters coverage: AI hyperscalers upend usual earnings stock swing pattern

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