With the market straining for decisively optimistic data, the news that second-week scripts for Foundayo generated only modest results led to a recent sharp decline in LLY stock. Fundamentally, the core distraction is that Wegovy — manufactured by Novo Nordisk (NYSE: NVO) — saw far more prescriptions in its second week than Eli Lilly’s new oral therapeutic.

That’s problematic from a patient experience standpoint because of a rising debate in efficacy between the two weight-loss drugs. According to a report cited by BioSpace, Wegovy (under the 25mg dosage) showed 3.2% greater weight loss than Foundayo. Thus, the implication is that, despite the arrival of the new competitor, patients will likely prefer the former drug.

However, the nuance here centers on logistics, of which Wegovy is a nightmare. Patients must take it on an empty stomach with exactly four ounces of water and wait 30 minutes before eating. On the other hand, Foundayo can be taken any time of day, with or without food. Eli Lilly believes this attribute offers a real-world advantage that will lead to superior long-term adherence.

From this angle, it’s quite possible that LLY stock could be undervalued — or is at least overly penalized by the “fear discount.” According to medical literature, when a therapeutic’s regimen becomes increasingly complicated, adherence becomes problematic. What the bulls are arguing for Eli Lilly, then, is that while Novo Nordisk may offer the slightly more effective drug, Eli Lilly brings to the table superior accessibility.

Another component that adds fuel to the fire is the upcoming Q1 earnings report, scheduled for April 30 (before the opening bell). If management can reveal data that supports its assertion that the long-term trajectory of Foundayo is more encouraging than recent reports have suggested, that could provide a strong catalyst for LLY stock.

An Inductive Approach to Analyzing LLY Stock

While the nuances behind Foundayo provide an intriguing narrative, it’s also difficult to fully understand how much of this dynamic has been reflected in Eli Lilly stock — if at all. There’s an assumption that if the pharma giant beats its headline numbers (earnings per share of $6.97 on revenue of $17.83 billion), LLY could be off to the races. However, that proposition likely depends on how much of the news has been baked into the share price.

Frankly, that methodology gets into a subjective game that’s difficult to assess quantitatively. That’s why I prefer a discretized inductive analysis to condition forward probabilities based on objective data.

Now, induction is really just a fancy term for pattern recognition. This philosophy relies heavily on the uniformity of nature, that whatever happened in the past is likely to repeat in the future. It’s another way of assigning correlations: should X happen, Y is likely to happen. Certain disciplines within technical analysis operate the same way. For example, if you see a head-and-shoulders pattern, that apparently signals a higher likelihood of a descending share price.

Unfortunately, the inputs of technical analysis are often extremely subjective, which is why I believe discretization is critical. By looking at discrete signals (such as the frequency of positive and negative weekly candlesticks), the data inputs of the underlying methodology are objective and consistent.

Personally, I run Markov simulations on potentially viable securities like LLY stock, which weigh forward probabilities based on the current behavioral state of the system. I define a state as a discretized 10-week period of price action. From there, I inductively calculate the probability of the next behavioral state materializing based on the current state.

In other words, I attempt to answer this question: given the last 10 weeks of price action, what is the likely forward distribution of the next 10 weeks? It’s the search for this answer where things get interesting for speculators.

Comparing Expectations Versus the Baseline for Eli Lilly Stock

On any given 10-week period, a trader holding LLY stock is likely to enjoy a noticeably strong upward bias. Out of 362 rolling 10-week sequences going back to January 2019, 233 of them popped higher than the starting price. This gives us an exceedance ratio of 64.4%. Further, the distribution of average outcomes would typically land LLY between $870 and $950, with probability density peaking at around $905.

However, we’re not interested in analyzing LLY stock as an aggregate of all possible 10-week sequences. Instead, we’re focused on the current signal. In the past 10 weeks, LLY printed only three up weeks, leading to an overall downward slope. Under this 3-7-D signal, the exceedance ratio jumps to 80%. Further, the forward distribution lands between $780 and $1,130.

Before you jump on the bullish bandwagon for Eli Lilly stock, a serious word of caution: we’re talking about a very small sample size of the aforementioned signal. Also, the forward distribution — based on a mixture of Bayesian-lite inference and conditioned historical data — does show expanded risk exposure (along with the enhanced reward profile).

Basically, LLY stock has become a high-risk, high-reward play — but the data (though diminutive in sample size) leans bullishly.

If you’re a diehard contrarian but rationally approach your trade through a quantitative lens, the idea to look into may be the 990/1000 bull call spread expiring June 18. This narrow spread requires LLY stock to rise through the $1,000 strike at expiration to be fully profitable. If it does, the maximum payout clocks in at 150%.

From a week-to-week Markov simulation, LLY historically has a tendency to rise in the latter weeks under 3-7-D conditions, making the $1,000 target potentially feasible. But it’s also fair to point out that a lot is riding on Eli Lilly’s earnings and how it frames Foundayo prescriptions. Ultimately, it’s a trade to consider if you don’t mind throwing caution to the wind.

Study after study reveals that obesity rates in the U.S. have risen for decades. According to data from the Centers for Disease Control and Prevention, many states now have obesity rates exceeding 35%, which is a threshold that was barely seen anywhere in the nation some 20 years ago. Subsequently, Novo Nordisk offers viable solutions with its flagship GLP-1 drugs, such as Ozempic and Wegovy.

Unfortunately for Novo Nordisk stakeholders, demand for the underlying company’s drugs has slowed this year, forcing management to revise its 2025 outlook multiple times. Further, the competitive environment is intensifying, particularly from sector rivals like Eli Lilly (NYSE:LLY). In addition, generics, combined with newer obesity-related therapies threaten Novo Nordisk’s pricing power and market share.

Still, the basic premise behind the bullish case for NVO stock is that the sell-off has been too severe. Since the start of this year, the security has dropped about 46%. Based on the principle of the reversion to the mean, NVO potentially has the makings of a comeback entity.

The problem, of course, is that this narrative is a well-worn one. But by digging into the quantitative data, we can look for empirical guideposts to help illuminate our speculative trading endeavors.

Objectifying the Price Discovery Process of NVO Stock

In most social contexts, objectification is a controversial term because it involves taking the richness of a person’s being and compressing their value down to their physical attributes. In the financial market, objectifying price action — such as treating all technical candlesticks as either up weeks or down weeks — also causes a loss of information and data fidelity.

Interestingly, though, if you wanted to conduct a sociological study — let’s say the influence of height as it relates to job applications — then objectification is a necessity. That’s because you would need some way to neatly classify otherwise unique individuals into discrete buckets of “tall” and “not tall.” It’s perhaps the ultimate irony that, in order to extract a greater truth, you must compress information to reveal a deeper structure.

As it turns out, multiple socioeconomic studies have found a positive correlation between height and labor market success in developed countries. For lack of a better phrase, the data points to tall privilege in society.

By the same logic, I hypothesize that there is a positive correlation between past price behaviors (or market stimuli) and specific future outcomes. If we’re being a bit cheeky, we might call this phenomenon heteroskedastic privilege — the idea that bullish or bearish structures will have a measurable influence on how future events will pan out.

Of course, if you look at any technical chart for NVO stock, you’ll notice that the security is represented as a singular journey across time. Obviously, it’s impossible to conduct probabilistic analysis on a sample size of one. But by segmenting price action into multiple rolling trials — a process known as sliding-window empirical distribution — we can convert a single technical chart into hundreds, if not thousands, of data points.

Primarily, the purpose of the sliding window process is to convert time-wise, continuous data (i.e. technical analysis) into time-and-state-anchored data, which is the heart of quantitative analysis. Thanks to this conversion, we can more easily calculate probability density — the price where the target security is most likely to land.

Leveraging the Geometry of Risk to Trade Novo Nordisk

Running the sliding-window process in a bespoke probabilistic algorithm, the forward 10-week median returns of NVO stock can be arranged as a distributional curve, with outcomes ranging between $46.60 and $48.12 (assuming an anchor price of $46.77, the most recent closing price). Further, price clustering would likely occur around $47.45.

The above assessment aggregates all windows or trials since January 2019. However, we’re interested in the current quantitative signal, which is the 3-7-D formation; that is, in the past 10 weeks ending Dec. 5, NVO stock printed three up weeks and seven down weeks, with an overall downward slope.

The sequence itself isn’t necessarily the important factor. Rather, based on prior observations, whenever NVO stock has printed the 3-7-D sequence, traders may expect the security to mostly range between $45.80 and $52.70 over the next 10 weeks, with price clustering likely to be predominant at around $49.80.

What’s just as fascinating about deciphering probability density is identifying the rate of probability decay. For example, between $50 and $51, NVO’s probability density declines by about 53.75%. From $51 to $52, however, density drops by 86.49%.

In other words, empirically minded traders are better off buying option premiums associated with the realistic side of the distributional curve — and selling the rest that is more fantastical and unlikely to materialize. In this manner, you would end up capitalizing the probabilistic meat of the trade while selling the sucker’s bet to someone else, thus discounting your net long position.

That’s essentially what’s going on with the 45/50 bull call spread expiring Feb. 20, 2026. This trade requires two simultaneous transactions: buy the $45 call and sell the $50 call, for a net debit paid of $234 (the most that can be lost).

Should NVO stock rise through the second-leg strike ($50) at expiration, the maximum profit is $266, a payout of almost 114%. While this is a capped-risk, capped-reward trade, since probability decay starts to rise exponentially after $50, we actually don’t want to pay for this premium.

Instead, we can sell it and discount the bullish position that is likely to emerge.

Playing the Numbers Game

While Novo Nordisk carries a compelling narrative, storylines alone usually aren’t great platforms for trading, particularly because of the obvious adage: if you’re reading about it in the news, the catalyst is probably already baked into the stock. Instead, my proposal is to run data analytics on NVO’s iterated price action to reveal patterns and structures. Through these observations, we may calculate the security’s next moves, thus giving us a huge advantage over other retail traders.