Uber Technologies (NYSE: UBER) isn’t exactly what you would call an enticing investment opportunity based on its current-year performance. Since the beginning of the year, UBER stock has dropped by almost 14%. Fundamentally, you would have to imagine that challenging economic circumstances have not aided the bullish thesis. Still, there might be an opportunity to extract quick profits through options.
At the time of writing, UBER stock trades hands at $70.47, with afterhours trading suggesting a modest decline to about $70.31 for Friday’s open. Ultimately, I’m seeing a positive volatility cluster that may offer an outside chance of UBER reaching $73 by the Aug. 21 expiration date — or about a 3.6% move from Thursday’s close.
First of all, what do I mean by a volatility cluster? Essentially, the price discovery process in the equities market is rarely orderly and linear. Instead, a ticker like Uber Technologies stock could see modest day-to-day moves, then swing sharply higher on certain sessions. A great example is an earnings report. Generally, you’re going to see a massive volatility cluster around a material financial disclosure.
Now, the ride-sharing giant has already disclosed its second-quarter results, leading to a sizable leap in UBER stock following a positive print. Of course, the sentiment from that Q2 report has been digested. What I’m suggesting is that another circumstance — specifically an order flow imbalance — could lead to another positive volatility cluster.
To be fair (and I need you all to pay attention here), the proposition is risky. Strangely enough, I’m going to demonstrate that the core trading idea I’m about to present features a negative expected value. Basically, this means that if you place a wager on this transaction across multiple parallel universes, you’d likely end up losing money.
However, I’m also going to demonstrate that among the rational debit spreads, the idea that I will propose is arguably the most efficient trade on a relative basis.
Diving into the Order Flow Balance of UBER Stock
What exactly is the order flow balance that I’m referring to for Uber Technologies stock? In the last 10 weeks, UBER managed to print only four up weeks, leading to an overall downward slope. When we filter historical trading data for this 4-6-D quantitative sequence, we notice an unusual characteristic in its forward 10-week behavior that we can potentially exploit.
If we were to assume a random walk for UBER stock over the next 10-week period, historical data suggests that the ticker’s median price could likely land between $69.50 and $72.50. At the week 10 endpoint, the most probabilistic price is between $71 and $72 — which isn’t much to brag about.
However, in the second week following the flashing of the 4-6-D signal, we tend to see a positive volatility cluster for Uber Technologies stock. Using an inductive approach, my guess is that there’s a solid chance that a similar scenario can repeat this time around.
Granted, we have to be careful here. Just because we witnessed a pattern in the past does not mean the trend is guaranteed to repeat in the future. Like all inductive models, the attempt to exploit order flow imbalances is prone to the black swan risk. It just takes one incident to go wrong for the model to look foolish.
Still, my main argument is that under certain conditions, a publicly traded security may undergo a nonrandom walk. And that’s the point here about UBER stock. Under 4-6-D conditions, there tends to be a nonrandom spike in week 2. I’m not guaranteeing that this volatility cluster will occur; rather, I’m just pointing to the history of such occurrences.
Plus, I’d like to point out that the concept of forecasting volatility clusters isn’t new. On July 29, I headlined an article on StockEarnings.com about a potential upsized move for Palantir Technologies (NASDAQ: PLTR). Now, I thought that PLTR stock was on pace to hit $127. It recently closed under $156. Nevertheless, the point still stands — a volatility cluster was signaled and a few days later it materialized.
Identifying a Tempting Idea
Having said all that, if the implications of the 4-6-D signal plays out as expected, the median endpoint price of UBER stock at week 2 is a little over $72. That means we may expect — assuming the implications of the model ring true — that half of outcomes may land above this point and half below. As such, the first instinct may be to consider a strategy involving $72 as an options-related target.
Still, arguably the most intriguing idea in the mix — which would be the 70/72 bull call spread expiring Aug. 21 — has a minor setback that might turn off some speculators. While the net debit is relatively cheap at $101 (meaning that this is the most that can be lost in the trade), the maximum profit should UBER stock rise through the $72 strike at expiration is $99.
If UBER’s odds of reaching $72 on Aug. 21 is indeed 50%, this would translate to an expected value of a loss of $1, stemming from this equation: (50% x $99) – (50% x $101) = EV. Obviously, the idea of suffering a negative EV isn’t exactly ideal. However, enhancing the reward potential only exacerbates the negative EV issue.
For example, you could push your luck with the Aug. 21 71/72.50 bull spread, which offers a max payout of over 111%. But because the probability of UBER stock reaching $72.50 at expiration (under my model) is only 43.4%, the reward isn’t enough to overcome the max profit/max loss split of $79/$71 into the positive side of the ledger.
To make a long story short, the return on risk for this trade would be about 19.57%, whereas the return on risk for the 70/72 bull spread would be less than 1%.
Yes, both options trading ideas lead to negative EV. However, if you are going to speculate, the 70/72 spread is more efficient against a risk-management framework.
A Final Note to Keep in Mind
I’m going to sound like a broken record but it must be stressed that prior patterns aren’t guaranteed to repeat. Nobody knows the future, especially when making a prediction in isolation. However, my belief is that certain market structures yield a tendency of nonrandom, asymmetric behaviors. If this behavior is divergent enough, we may be able to exploit it. That’s possibly the case with UBER stock.
