Options Corner: Using Applied Calculus To Pinpoint A Bullish Trade For JD.com

At first blush, Chinese e-commerce enterprise JD.com, Inc. (NASDAQ:JD) seems to have cast a dark shadow over bullish investors. For one thing, the performance of JD stock hasn’t been all that great, losing more than 13% on a year-to-date basis. Difficulties in U.S.-China trade relations impose a harsh light on the business. If that weren’t enough, unusual options activity apparently points the forward trajectory in the wrong direction.

Just hours ago, deep-pocketed investors — commonly known as whales — appeared to have taken a bearish stance against JD stock. Specifically, among big block transactions, 66% of the order flow appeared to have bearish leanings while only 11% appeared to be net bullish. Given not only the broader weakness of JD shares but also near-term volatility — with the security losing about 8.5% in the trailing month — the options data represents a possible warning.

Still, we need to be careful about reading too deeply into one dataset. First, rumblings in the options market change like the wind. For example, at the end of last week, the whales were apparently bullish on JD stock. And about a week-and-a-half before that session, these alpha dogs of the market appeared to be net optimistic.

Second, retail investors are privy to knowing what the legs of the major derivative transactions are but they don’t know what the intent is. It’s possible that the volume could be tied to a directional wager. At the same time, it could also be a hedging activity or it could be part of a multi-leg options strategy, such as a vertical spread or condor.

Ultimately, making a decision on JD stock just based on one screener wouldn’t be prudent because it effectively violates Ashby’s Law of Requisite Variety. Basically, a complex system requires a methodology of adequate rigor to explain it. Simply buying or selling JD based on a single options readout would not meet the necessary epistemological standard.

Pulling Out Trinitarian Geometry To Trade JD Stock

As a stochastic, chaotic, heteroskedastic and reflexive ecosystem — among many other esoteric descriptions — the equities market ranks among the most complex paradigms. Because of this reality, we can’t just use the middle-school math that undergirds much of fundamental analysis. Instead, we need to have a methodology that addresses most of the technical nuances of market behavior.

To better achieve this goal, I came up with a framework that I’m now calling trinitarian geometry. Specifically, this approach integrates probability theory (inspired by the work of Andrey Kolmogorov), behavioral state transitions (Andrey Markov) and calculus (kernel density estimation or KDE). Primarily, the purpose of using trinitarian geometry is to calculate probability density or the point where prices tend to cluster given enough trials.

Of course, the difficulty is in the format. Because a stock represents a singular journey across time, this format doesn’t lend itself organically to probabilistic analysis. To get around this dilemma, we can reify probability as a physical object — and to do that, we iterate price action as a series of sequences or trials.

Using the trinitarian geometry mentioned above, the forward 10-week returns of JD stock can be arranged as a distributional curve, with outcomes ranging between $29.10 and $31.40 (assuming an anchor price of $29.83, Friday’s close). Further, price clustering would likely be prominent at $30.40, indicating a modest bullish bias.

The above assessment aggregates all trials since January 2019. However, we’re interested in the statistical response based on a specific signal, the 4-6-D formation; that is, in the past 10 weeks, JD stock printed four up weeks and six down weeks, with an overall downward slope.

Under this setup, the forward 10-week returns of JD stock would be expected to mostly range between $29.20 and $31.40, with price clustering expected to be most prominent at $30.50. What makes JD specifically intriguing is that the 4-6-D formation represents 20.23% of all sequences that have flashed in the dataset.

In other words, because of the subset sample size, the price density being the thickest or heaviest at $30.50 is a much more reliable indicator than it would normally be for a less robust dataset.

Targeting An Aggressive Trade

Armed with the information above, the most aggressive trade that still makes sense may be the 30/31 bull call spread expiring Jan. 16. This wager requires two simultaneous transactions on a single ticket or execution: buy the $30 call and sell the $31 call, for a net debit paid of $49 (the most that can be lost).

Should JD stock rise through the second-leg strike ($31) at expiration, the maximum profit is $51, a payout of over 104%. Further, breakeven comes in at $30.49, which is right smack dab at the heart of where probability density is projected to be at its thickest.

Basically, the trade banks on the empirical observation that, given enough trials of the 4-6-D sequence, prices tend to cluster at $30.50. We’re then hoping for a little bit of luck, just a nice tailwind to drive the price toward the upper end of the distributional curve and hit $31. If not, we still have a good chance of breaking even and thus avoiding ruin.

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