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Today's editorial pick for you
When Trading Oracle (ORCL) Stock, Don't Fall for the 'Babe Ruth Fallacy'
Posted On Dec 24, 2025 by Joshua Enomoto
For a data-driven options trader, nothing can be more exciting than tech giants like Oracle(NYSE: ORCL) stumbling due to what may arguably be considered misguided fundamental concerns. True, ORCL stock has incurred recent volatility, leading to a trailing six-month loss of roughly 6%. While the actual correction isn't terrible, it does bring the year-to-date return to only 17.22%.
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To put this into some unfortunate context, the Nasdaq Composite index is up 22% during the same period. That's not exactly a great situation to be in when you're supposedly one of the vanguards of applied machine learning.
So, what's the deal with ORCL stock? While the financial publication industry features multiple opinions, the gist of the narrative is that investors believe the low-hanging fruit of artificial intelligence has already been plucked. As a result, the rise in capital expenditures toward generative AI has many investors pumping the brakes — likely stemming from reflexive trauma of past boom-bust cycles.
Of course, you never want to blindly assume that this time it's different. Admittedly, those are some dangerous words in finance. At the same time, AI is different from past cycles of exuberance. It's not just an innovative solution. When used correctly, AI accelerates both productivity and the intellectual capacity of its users.
That's the reason why companies and even countries are deeply invested in machine learning. Dominance in this sphere can yield radical paradigm shifts across industries. In that framework, ORCL stock represents a long-term investment. However, what makes Oracle appealing is that it's also signaling for upside in the near term.
Throwing Out Old Assumptions
I'm going to get in trouble for saying this out loud, but I'm sure you've all seen various businesses selling advanced technical analysis charts. Well, that business — in my humble opinion — is kind of like saving up money to buy a taxi medallion right before ride-sharing services disrupt the industry. It's a terrible waste of funds because these charts don't tell you anything other than what everybody else already knows.
When you look at any price chart, you are merely seeing price action being plotted against time. Therefore, unless the analyst or author specifies otherwise, the reader (i.e., you) has no other assumption to work off of other than to presume a constant sentiment regime. I call this the "Babe Ruth Fallacy."
If you talk to old heads (especially if they're from New York), they'll bristle at the notion that Shohei Ohtani is the GOAT (greatest of all time). They'll insist that Babe Ruth is the GOAT because one year, he hit more homers than entire teams — and if Ohtani were to duplicate such a feat today, he would need to hit 700 jacks in one season.
Such a ridiculous, bad-faith counterargument assumes that the state or function of competition remains constant across time. That's obviously not true. Modern Major League Baseball (MLB) represents the most elite version of the sport. Therefore, Ohtani's achievements have been earned in the most difficult competitive state of baseball. To say otherwise is to ignore the vector of human athletic evolution.
Similarly, we cannot assume that the sentiment regime of a tech name like ORCL stock stays constant across a dataset extending multiple years. For example, Oracle's five-year chart likely shows multiple sentiment regimes — and we're not just talking bullish and bearish cycles. We're talking about specific degrees of optimism and pessimism.
But in 99% of cases, analysts — especially technical analysts — in the public-facing financial media are either working off the assumption of a single constant regime or worse yet, eyeballing regimes based on intuition and vibes.
There's a better way — a mathematical way — and that's what we're going to explore next.
Identifying the Risk Geometry of ORCL Stock
One critical problem that prevents organic classification of price behavior into identifiable sentiment regimes is that price itself is a continuous signal. However, classification necessarily requires objectification — because obviously you can't classify infinity. That's the main reason why I convert price behavior into sequencing logic, so to speak.
Without the sequencing logic, there's no way to classify different behavioral sets.
Following this discretization process, we must view price action hierarchically. Consider a single 10-week strand of ORCL stock. Clearly, the return during this period won't tell us anything about the probability of performance of the other weeks in the dataset. But what if we stacked hundreds of rolling 10-week trials in a fixed-time distribution? In this case, the most consistent, frequent behaviors will create bulges in probability mass.
This bulge is risk geometry, which reveals the accelerating sentiment of optimism among buyers. More importantly, it reveals the point where buyers are tempted to become sellers. Therefore, we have a better idea of where to push — and where to back off.
Using this hierarchical process, the forward 10-week returns of ORCL stock are likely to range between $190 and $210 (assuming an anchor price of $195.34, Tuesday's close). However, we're more interested in the bimodal distribution created by the current quantitative signal, which is the 3-7-D sequence. In the trailing 10 weeks, ORCL only printed three up weeks, leading to an overall downward slope.
However, under this condition, the forward 10-week returns would likely range between $192 and $220, with price clustering predominant at roughly $207. What's most intriguing is that probability mass is thickest between $200 and $210.
Picking Out the Best Idea for Oracle Bulls
To be sure, with so many options-based ideas available, picking one strategy over another comes down to a combination of individual preference and risk tolerance. That said, if you want to know the most rationally aggressive wager, my vote would go toward the 200/210 bull call spread expiring Feb. 20, 2026.
The reason why comes down to the rate of probability decay. Between $205 and $210, probability density declines on a relative basis by 23.38%. Between $210 and $215, density drops by a stunning 84.3%. Effectively, this means that by capping the upside potential at $210, the chance of you absorbing an opportunity cost is minimal compared to a lower strike price.
Stated differently, the 200/210 spread allows you to buy the reality and sell the fantasy.
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