Options Corner: Why Uber Technologies Stock's Risk Geometry Backs A More Aggressive Trade

Recently, ride-sharing juggernaut Uber Technologies, Inc. (NYSE:UBER) saw its market value rise following an announcement that Dallas riders can now book an Avride robotaxi, thereby offering an autonomous mobility solution. In the past five sessions, UBER stock is up 4%. However, the security is still off by roughly 10% since early October.

As it stands, UBER stock remains stymied by earlier jitters in the broader technology space — anxieties that have forced several experts to brush aside fears of a bubble. There’s also the matter that consumers feel bleak about the economy, even though recession risks have subsided. Obviously, negative sentiment could easily impose headwinds on people’s willingness to order rides (which isn’t exactly the cheapest form of mobility).

Still, what ultimately matters for near-term options traders is whether any of the fundamental catalysts undergirding UBER stock translate into probabilistically high directional outcomes. To find out, we can use creative methodologies to understand where prices are likely to coagulate or cluster.

Going beyond standard methodologies, we can break apart UBER’s price action and convert them — as part of a conceptual exercise — as projectiles, such as cannonballs. The idea is to fire these cannonballs into an open field. After hundreds of discharges, there should be a point in the field where the projectiles feature the tightest grouping.

In mathematical or scientific language, that would be called probability density.

However, we’re not necessarily interested in just the place where all fired cannonballs will most likely be dispersed. Instead, we want to know the grouping of a specific set of cannonballs — the signal that we’re isolating for. If this set features different groupings relative to the aggregate, we may have a structural arbitrage.

Stated differently, most of the market would be expecting the aggregate outcome while you have calculated a different outcome.

Extracting Insights For UBER Stock Using The Shape Of Risk

As you might imagine, conducting the cannonball exercise requires extensive math, a process I call trinitarian geometry. For the curious, it combines probability theory (Kolmogorov), behavioral state transitions (Markov) and calculus (kernel density estimations).

Frankly, it just boils down to understanding the likelihood of a directional outcome materializing in a chaotic, non-linear world. While the concept will take some time to fully absorb, I truly believe that understanding the science opens a whole new world of insight.

In particular, we can now identify and analyze the shape of risk. This changes everything.

Using trinitarian geometry, the forward 10-week returns of UBER stock will likely range between $89 and $95.20 (assuming an anchor price of $90.34). Further, price clustering would likely occur at $91.

The above aggregates all trials — or cannonball discharges, to extend the analogy — since Uber’s initial public offering. However, we’re interested in a specific signal, the 4-6-D sequence; that is, in the trailing 10 weeks, UBER printed four up weeks and six down weeks, with an overall downward slope.

Under this circumstance, the forward 10-week returns would likely range between $88 and $95.20, with price clustering likely to be predominant at $91.50. To be honest, a half-a-percent positive variance is a structural arbitrage that isn’t worth writing home about. But what’s really interesting is the shape of the risk curve.

Starting from $92 onward, for every dollar that the price increases, the drop-off in probability density occurs at a super-linear rate. For example, between $92 and $93, probability density declines by approximately 31.25%. Between $93 and $94, the erosion is about 77.73%. From $94 to $95, the decline sits at 98%.

However, it’s also fair to point out that the shape of risk bulges outwardly at the belly — thus the curve almost resembles a shark fin. This geometric shape implies that we could be a little bit more speculative with our options trade.

Math Is Our Ultimate Guide

If we just had the cannonball clustering data, we might be tempted to go for the relatively conservative idea of the 90.00/92.50 bull call spread expiring Jan. 16, 2026. This trade would require UBER stock to rise through the second-leg strike ($92.50) at expiration, which is contextually a realistic target. However, the maximum payout is only 85.19%, which is decent — but can be improved upon.

For those that really want to go for it, the 90/95 bull spread, also expiring Jan. 16, could be an intriguing proposition. Here, the breakeven price stands at $92.25, which is practically right at the point where the probability density is about to drop off severely.

Put another way, we would be buying the call premiums that are associated with the realistic side of the distributional risk curve, the slices that are likely to materialize. Simultaneously, we are going to sell the portion of the risk curve that is least likely to materialize.

To be sure, UBER stock would need to rise through the $95 target at expiration to trigger the maximum payout of over 122%. That’s admittedly an ambitious target. However, we would also sleep a bit easier knowing that UBER’s curvature bulge may give us a fighting chance for a big payout — but also limits the opportunity cost of the stock rising above $95.

While there’s nothing preventing UBER from going above this point, the empirical data shows that it’s less likely. But ultimately, we wouldn’t have this knowledge if we didn’t calculate the shape of risk. As I said earlier, this changes everything.

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.

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