Software giant Oracle (NYSE: ORCL) has been an extraordinarily difficult name to figure out. Although the company benefited handsomely from the broader artificial intelligence narrative, rising concerns about capital expenditures and sustainability within the sector have been particularly harmful to ORCL stock. As evidence, the ticker is down more than 27% on a year-to-date basis despite Monday’s big swing higher.
However, we can’t ignore the implications behind the beginning-of-the-week catalyst. According to a BlockOnomi report, ORCL stock popped 9.22% to $141.85 as two Ontario hospitals advanced a shared Oracle Health electronic record project. As the article explains, the “partnership gives Oracle another major healthcare deployment across complex hospital and outpatient settings.”
Of course, the usual routine within the financial publication ecosystem is to wax poetic about a news event that happened in the past. Yes, the practice may be useful for those who want a quick overview of the material facts. Still, the meta concern is that when people read finpub articles about ORCL stock, they’re usually not looking for an autopsy.
Instead, they’re seeking ex-ante insights; that is, probabilistic forecasts about what might materialize in the future.
Think of it this way. When you check the five-day weather report, are you interested in yesterday’s weather? No, of course not! You want to know what’s on the horizon so you can better plan ahead. And while we recognize that the meteorologist isn’t always right, we have a better understanding of future outcomes through this probabilistic discipline.
It’s the same principle with options trading. You don’t care about what happened to ORCL stock yesterday. You want to know what is likely to occur in the days ahead. That way, you can research the proposition — and if you should please — place a trade before the expected move occurs.
But is there such a tool that’s available for retail traders? Yes, it’s the Markov simulation — and we’re witnessing a sort of backtest of the model for Oracle stock right now.
ORCL Stock Had Already Flashed an Upside Signal
It’s not talked about in the mainstream financial media industry but Oracle stock had already tipped its cards. In the middle of last month, I wrote that ORCL had “flashed a meaningful quant signal for the bulls.” In particular, the signal was that in the prior 10 weeks, ORCL had only printed three up weeks, thus leading to an overall downward slope.
Now, I think most folks, if they recognized the 3-7-D quantitative sequence, viewed the matter as a statistical quirk. But here’s the insight. Whenever this condition occurred, ORCL stock had previously exhibited a tendency to eventually pop higher than what would be expected under a random 10-week hold.
In the article, I wrote the following: “Specifically, week 6 following the flashing of the 3-7-D signal features the highest median expected value at just above $140. Thus, if we’re trading purely based on the inductive data, the natural play would be to consider the 135/140 bull call spread expiring Aug. 21.”
As of the close of Aug. 3, ORCL stock (as mentioned earlier) closed at $141.85. Looking at the afterhours data, the ticker has moved to $142.62 at the time of this writing. Assuming that Oracle can trend sideways from here, there’s a solid chance that the Aug. 21 135/140 bull spread will be fully profitable.
Keep in mind that I had zero knowledge about the Ontario hospitals catalyst when I mentioned the idea. I just know from past empirical data that, under the same conditions that Oracle stock found itself in, the ticker has a tendency of rising.
Without getting bogged down by the math, that’s the Markov principle that undergirds my simulated model. I’m not saying that I can tell the future. Rather, when ORCL stock finds itself in unique quantitative circumstances, we can use past analogs and inductive analytics to better forecast where the security may land.
And no, the Markov simulation isn’t perfect — far from it. When you look at the July 15 forecast juxtaposed with actual ORCL data, you can clearly see that Oracle stock fell much more sharply than anticipated (down to $114.99 at the end of week 2 (July 24). But notice how in the following week, ORCL bounced back into the expected range of historical outcomes.
Random vs Non-Random Walk
Another key reason why I’m a proponent of Markov models is that they largely assume path-dependent trajectories. Many of you are familiar with the options pricing model known as Black-Scholes. When Wall Street talks about probabilities, these are implied probabilities based on the Black-Scholes family of calculations, which assume that equities take path-independent trajectories.
In a nutshell, whenever Black-Scholes is invoked, traders are asking a specific question: assuming today’s implied volatility (IV) — or the market’s expectation of forward movement — what is the probability that the target security will reach a certain price point at a certain expiration date, assuming that the ticker in question takes a random walk?
Based on whatever that probability is, the Black-Scholes architecture allows traders to back out the assumptions that were used to calculate the aforementioned implied probability to arrive at fair price today. So, if your options spread has a low probability of profit (say 30%), then the price that you pay for that trade today is going to be relatively cheap — because the price reflects the low odds of breaking even in the future.
Here’s where the tension lies, though: we know through observation that equities are likely not taking a random walk. Instead, when you look at a highly mobile name like ORCL stock, such securities are taking nonrandom walks — and they’re liable to take nonrandom jumps during major news events.
And that brings the discussion back to Markov simulations. I demonstrated that when Oracle stock prints specific quant sequences, its trajectory is typically no longer defined as a random walk but a nonrandom walk. What the core benefit is about Markov models is that we have a solid idea of how nonrandom the movement may be — and for the daring, we can place trades ahead of time to exploit the forecasted move.
Another Opportunity for Oracle Stock?
I’m excited about ORCL stock because it just flashed another intriguing quant sequence. In the past 10 weeks, ORCL has printed only two up weeks, thus leading to a downward slope. Under this 2-8-D condition, we may expect — based on historical trends — a gradual rise toward week 6.
For your reference, I provided a fresh Markov simulation about what we may expect over the next 10 weeks. Of course, the usual caveats apply. I’m not guaranteeing anything and Oracle stock is not logically forced to follow past patterns. But if you give some credence to inductive analytics, you may consider a speculative position.
One idea may be the 145/150 bull call spread expiring Aug. 28. This trade requires ORCL stock to rise through the $150 strike at expiration to be fully profitable, with the max payout standing at a little over 104%.
Mathematically, the key to this trade is the $147.45 breakeven price. Wall Street pegs a probability of profit of only 41.3%. That’s assuming ORCL stock takes a random walk toward the profitability threshold. However, I’m assuming a nonrandom walk.
Of the five times that the ultra-rare 2-8-D sequence has flashed since January 2019, Oracle stock exceeded the equivalent of the $147.45 breakeven price a total of three times at the end of week 4 (Aug. 28). Technically, that’s 60%, although there’s a huge caveat in that the sample size is extremely small.
Nevertheless, my argument would be that the rarity of the signal is part of its strength. Theoretically, trading algorithms should view this extended bearishness as a discounted opportunity, thus bidding up ORCL stock now that the weak hands have been flushed out. It’s still very speculative but it may be worthwhile for risk-takers to consider.
