While representing one of the most actively traded securities recently, ServiceNow (NOW) stands on unusual ground. After a few months of struggle amid uncertainties about how the Trump administration would navigate the economy, the broader technology space rebounded sharply since early April. To be sure, NOW stock also benefited from the uptick.
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However, as various innovators reached record valuations, ServiceNow has become one of the tech sector’s laggards. On a year-to-date basis, NOW stock is down more than 13%. In the past 52 weeks, it has gained less than 10%. Even its five-year return of nearly 104% isn’t overwhelmingly impressive compared to other companies serving the broader digitalization push.
As such, the cloud-computing platform, which specializes in creating and managing automated business workflows, has something to prove. At the same time, the company’s earnings and revenue growth exhibit a steady upward trend. Also, ServiceNow has become more financially stable over the past few years, as noted by the declining debt-to-assets ratio.
For traditional buy-and-hold investors, there could be an opportunity to acquire shares at a relative discount. However, for the most intrepid speculators, NOW stock may feature favorably mispriced call options. Therefore, I am Bullish on ServiceNow and will attempt to demonstrate how you can capitalize on this pricing mismatch.
Two Schools of Thought in Deciphering the Options Market
Before diving into the complex world of options, it’s helpful to get a proper framework. Primarily, there are two schools of thought regarding the assessment of risk in the options market, with one of these methodologies being the overwhelming favorite in modern markets.
For most options traders, they will be familiar with parametric models. These are frameworks that assume a particular distribution and structure for returns, most commonly the log-normal distribution of stock prices used in the Black-Scholes-Merton (BSM) model. Further, derivative concepts — such as implied volatility — stem from the BSM formulation.
As you might imagine, BSM is popular because most of the scaffolding is already built. In other words, the structure is closed form: all you have to do, then, is to plug in current market price data, and the formula delivers projected options-related values. However, the issue is that these projections are presuppositional in nature.
There’s also the significant issue that the BSM model isn’t a predictive tool in the conventional sense. Instead, it determines how much options premium the debit buyer should pay (or how much premium a credit seller should receive) for both calls and puts. Professional traders create their own proprietary options pricing models to determine if there is an asymmetric delta to exploit between the standard premium pricing and the “real” pricing.
Going the Non-Parametric Route
Fundamentally, non-parametric models diverge from parametric frameworks by letting the data speak for itself. Put another way, non-parametric models don’t assume that the observed dataset falls under a specific distribution, such as Gaussian. As such, it’s a mathematically messier model, requiring intensive computing power. That’s because under a non-parametric model, each dataset is unique — there is no prebuilt scaffolding.
When it comes to evidence, the “expected move” calculators used by options-focused platforms tell the tale. The charts all look the same: a funnel that extends outward. Simply, the reason is that the mathematical scaffolding is practically identical, with the difference mainly being the open-market share price of the stock being examined.
With non-parametric models, each stock has its own unique distribution. This is incredibly intensive from a computational standpoint, yet it can also lead to analyses that cannot be extracted by any other means.
Identifying the Options Pricing Mismatch in NOW Stock
Using a non-parametric analysis of NOW stock, it’s possible to map out what may happen in the future based on the security’s actual pricing geometry. Through this methodology, NOW is expected to have a natural drift between a median low of $937.32 and a median high of $1,006.15 over the next 10 weeks.
To be sure, NOW stock can easily drive beyond these given ranges. However, based on past pricing behaviors, the stock is expected to typically settle at one of these price levels as a median expectation.
However, NOW stock has printed a rare quantitative signal over the last 10 weeks, where the market essentially voted to buy the security six times and sell four times. During this period, NOW incurred a downward trajectory. For classification purposes, we can label this sequence 6-4-D.
Typically, in the week following the flashing of the 6-4-D, the price action rises only 28.6% of the time. However, over the next several weeks, this non-parametric volatility skew tends to swing violently higher. It must be stated with 100% clarity that there’s no guarantee that NOW stock will follow this upward skew. Nevertheless, based on the conditional probability of the 6-4-D sequence flashing, the bulls arguably have the edge.
With that in mind, the one trade that stands out is the 980/990 bull call spread expiring October 17th. This transaction involves buying the $980 call and simultaneously selling the $990 call, for a net debit paid of $380 (the maximum possible loss on the trade).
Should NOW stock rise through the short strike price of $990 at expiration, the maximum profit is $620, a payout of over 163%.
Is NOW Stock a Buy or Sell?
Turning to Wall Street, NOW stock carries a Strong Buy consensus rating based on 28 Buys, three Holds, and one Sell rating since June. The average NOW price target is $1,154, implying almost 26% upside potential over the coming twelve months.
Looking at NOW Stock in a New Light
Typically, options traders rely on parametric models to decipher potential opportunities in the options market. However, the issue here is that such frameworks are incredibly complex and can be misleading because they assume a distribution that may not be accurate. With non-parametric models, the framework is more computationally intensive but can potentially lead to more accurate analyses.
My argument is that NOW stock, under a non-parametric lens, demonstrates an asymmetry between commonly expected results and what could actually happen based on the flashing of a rare quantitative signal. As such, intrepid speculators may want to keep their eyes focused on ServiceNow this week.