Among companies related to the artificial intelligence boom, information technology specialist Hewlett Packard Enterprise (NYSE:HPE) isn't exactly the first name that comes to mind. That's mainly because the company isn't a frontline semiconductor enterprise but is rather a provider of critical infrastructure. Nevertheless, the steep sell-off in the tech space has been disruptive, with HPE stock down about 10% in the trailing month. Despite the pain, though, there could be a contrarian opportunity in the mix.
Fundamentally, Hewlett Packard might benefit from a broad, recurring catalyst rather than a single hypersensitive product cycle. Sure, companies like Nvidia Corp (NASDAQ:NVDA) tend to grab most of the headlines. At the same time, their price discovery process can be peaky. However, Hewlett Packard is in the business of AI infrastructure — servers, networking, storage, data pipelines and similar systems. These elements represent multi-phase, multi-year build-outs across both enterprises and government agencies.
In other words, an investment in HPE stock is more about targeting longer-duration revenue rather than going all out for a kill shot.
More recently, HPE stock has looked alive, gaining over 3% during Monday's afternoon session. Primarily, market sentiment shifted decisively after Federal Reserve policymakers broadcasted dovish remarks. Specifically, New York Fed President John Williams and Governor Christopher Waller separately delivered commentary that implied an accommodative stance.
Subsequently, traders now assign a 77% chance to a 25-basis-point cut at the Dec. 10 Fed meeting. Previously, the odds were 71% on Friday and only 25% one week ago.
Finally, Hewlett Packard is set to release its fourth-quarter earnings on Dec. 4 after the market close. Given its recent history of delivering the goods, along with key partner Nvidia posting a blowout third quarter, circumstances seem auspicious. If the company comes through again, HPE stock could potentially pop.
Leveraging The Concept Of Probability Density To Trade HPE Stock
While the above narrative undergirding Hewlett Packard may sound compelling, the core concern would be that opinions rarely provide much insight. Whatever is known about a security has likely been priced into it, especially a major name like HPE stock.
Moreover, from a mathematical perspective, fundamental analysis provides almost zero empirical utility because the methodology merely plots a financial performance metric as a function of time. Since time is a constant, the fundamental approach is simply a record of what happened in the past. To automatically assume that this data has predictive power is flawed logic unless the author can demonstrate a correlation between historical archives and forward-looking assessments.
Instead, to trade HPE stock effectively, we need to understand its tendencies; more to the point, we must identify where HPE is likely to cluster given enough trials and under specific circumstances or conditions. This metric that we're looking for is called probability density.
Unfortunately, probability density isn't a simple metric to calculate like earnings per share or any other hackneyed valuation indicator. First, the dataset must be broken down into trials or sequences (I prefer 10 weeks). Second, a mathematical system involving a Kolmogorov-Markov framework layered with kernel density estimations (KM-KDE) must be applied. Together, these processes allow us to plot probability density as a function of price.
Here’s what the math looks like in practice. Using the KM-KDE approach above, we can arrange the forward 10-week returns of HPE stock as a distributional curve, with outcomes ranging between $21.17 and $21.50 (assuming an anchor price of $21.16). Further, price clustering would likely be predominant at $21.29.
The above assessment aggregates all trials since January 2019. However, we're interested in the statistical response to the 4-6-D signal; that is, in the past 10 weeks, HPE stock printed four up weeks and six down weeks, with an overall downward slope.
Under this sequence, forward 10-week outcomes would range between $20.50 and $22.80. More importantly, price clustering would be predominant at around $21.30, with secondary clustering occurring at $22.
To be fair, there's no real variance between the baseline and situational clusters. However, the probability density is thicker and more massive on the reward side of the distributional curve rather than the risk side. As such, we have greater confidence in a bullish directional wager.
Taking A Measured Bet On Hewlett Packard Enterprise
Given the statistical outlook that we calculated for HPE stock, we have a clearer idea of the security's risk-reward profile. With all things considered, arguably the most appealing trade is the 21/22 bull call spread expiring Jan. 16, 2026. This wager involves two simultaneous transactions conducted as a single ticket (execution): buy the $21 call and sell the $22, for a net debit paid of $51 (the most that can be lost).
Should HPE stock rise through the second-leg strike ($22) at expiration, the maximum profit is $49, a payout of over 96%. Breakeven comes out to $21.51, which is near the densest part of the 4-6-D sequence's forward distributional curve.
As you can see, with this quantitative approach, we don't base our decisions on hopes, dreams and empty rhetoric. Instead, we deploy advanced mathematics to calculate the structure of HPE's probability density curve. By analyzing density as a function of price, we can identify the price point that gives us the best chance for success while collecting the highest reward possible.
The opinions and views expressed in this content are those of the individual author and do not necessarily reflect the views of Benzinga. Benzinga is not responsible for the accuracy or reliability of any information provided herein. This content is for informational purposes only and should not be misconstrued as investment advice or a recommendation to buy or sell any security. Readers are asked not to rely on the opinions or information herein, and encouraged to do their own due diligence before making investing decisions.
Read More:
Image: Shutterstock
- No comments yet. Be the first to comment!