Just when the market seemed comfortable with artificial intelligence valuations, the bubble fears came roaring back. Marvell Technology Inc. (MRVL) got caught in the crossfire. The semiconductor company enjoyed a fantastic run from September through early December, climbing roughly 41%. Then reality hit. Since closing out on Dec. 3, shares have tumbled about 18%.

What triggered the reversal? Nobody truly knows the precise formula behind price discovery, given the gazillions of variables at play. But the prevailing narrative points to renewed anxiety about AI spending, sparked by Oracle Corp (ORCL) and its latest earnings report.

Heading into that disclosure, analysts had positioned Oracle's results as a bellwether for AI-adjacent investments across the board. They weren't wrong. Oracle delivered a mixed message that sent Wall Street into a mini-panic, dragging down multiple semiconductor stocks in the process. The core concern centers on whether AI capital expenditures have gotten ahead of themselves, with companies potentially overcommitting to infrastructure before demand fully materializes.

Yet bullish observers argue we're still in the early innings of the machine learning revolution. There's scant evidence that genuine interest in AI is fading. If anything, competition is intensifying, particularly around critical supply chains that enable AI development. The technology isn't going anywhere.

Which brings us to another reason for optimism around Marvell: the Santa Claus rally.

This well-documented seasonal pattern typically sees equities push higher during the stretch between Christmas and the first trading days of January. The phenomenon stems from lighter trading volumes, tax-driven portfolio adjustments, and general year-end optimism. While the Santa Claus rally traditionally favors established blue chips over volatile tech names, the underlying market dynamics could still provide a lift for beaten-down stocks like Marvell.

And there's another statistical pattern worth considering that might favor the semiconductor company right now.

The Case For Buying Marvell's Dip

Most market analysis plots price as a function of time. But price is really a function of state—the collective weight of countless variables driving price discovery at any given moment. The challenge is that nobody knows which factors matter most, or how they're weighted in the grand equation.

We can't identify the precise causal state driving market behavior, but we can measure its projected impact. Think of stocks like asteroids. We don't fully understand where asteroids originate in the cosmic sense, but we can calculate the damage they'd cause upon impact.

Using a similar approach, we can take Marvell's continuous price history and split it into multiple rolling sequences. Instead of analyzing one giant asteroid trajectory, we're examining hundreds of potential pathways distributed across fixed timeframes. This method lets us measure the median potential outcome across those scenarios.

Looking at all 10-week returns for Marvell since January 2019, the median distribution suggests a range between roughly $80 and $88, assuming an anchor price around $82. Price clustering would likely concentrate near $84.80 under normal conditions.

But the current pattern is more specific. Over the trailing 10 weeks, Marvell printed just three winning weeks against seven losing ones, creating a clear downward slope. We can isolate this particular sequence—call it the 3-7-D pattern—to understand what typically happens next.

On the surface, this selling-pressure-heavy sequence looks bearish. However, historical analogs reveal something interesting. When buy-the-dip sentiment kicks in after similar patterns, the forward 10-week distribution actually stretches wider, from $78 to $90. More importantly, price clustering shifts upward to around $85.80, a full dollar higher than under aggregate conditions.

In other words, stocks that get beaten down like Marvell has recently tend to bounce back more strongly than the average return would suggest.

Translating Statistics Into A Trade

Based on this distributional approach, we can project that Marvell is likely to climb from around $82 to $86 over the next 10 weeks on a median basis. Just as importantly, while hitting $90 or above isn't impossible, historical patterns suggest the probability of sustaining those levels is minimal.

This is what you might call risk geometry—the structure of risk and reward mapped across a specific time horizon. As far as quantitative approaches go, this distributional lens offers insights that traditional technical analysis often misses. It shows you not just where price might go, but the probability landscape of various outcomes.

Given this statistical picture and the potential tailwind from seasonal Santa Claus dynamics, here's a specific trade worth considering: the 85/87.50 bull call spread expiring Jan. 16, 2026.

This position involves two simultaneous transactions executed together. You buy the $85 call option and simultaneously sell the $87.50 call option, paying a net debit of $100 (which represents your maximum possible loss).

If Marvell stock rises above the upper strike of $87.50 by expiration, the maximum profit hits $150—a 150% return on the initial investment. The breakeven point lands at $86, which aligns well with the median projection from the distributional analysis.

Why not push for higher strikes to capture more upside? Because between $86 and $88, probability density drops by roughly 75.67% according to historical patterns. Stretching the breakeven threshold higher would mean chasing exponentially declining probabilities. You'd be paying premium for outcomes that rarely materialize.

When you calculate risk geometry properly, you gain the advantage of making informed, efficient decisions rather than gambling on low-probability outcomes. The goal isn't to hit home runs on every trade—it's to structure positions where the probabilities and payoffs align favorably with what the data actually suggests is likely to happen.

Marvell has taken a meaningful hit on AI spending concerns that may prove overblown. The technical patterns suggest a rebound over the coming weeks, and seasonal dynamics could provide an extra nudge. For options traders comfortable with defined risk, this setup offers an asymmetric opportunity where you risk $100 to potentially make $150, with the probabilities leaning in your favor based on how similar patterns have resolved historically.

Of course, past patterns don't guarantee future results, and the AI narrative could deteriorate further if more companies signal pullbacks in infrastructure spending. But for contrarian traders looking to capitalize on what might be an overreaction to Oracle's mixed signals, Marvell's current setup presents an interesting case study in applying statistical analysis to options strategy.