One of the key difficulties of analyzing highly kinetic enterprises like IonQ Inc (NYSE:IONQ) is that their valuations incur reflexivity. A concept popularized by George Soros, reflexivity is a phenomenon where investor perceptions constantly influence each other in self-reinforcing feedback loops. Subsequently, this dynamic can cause prices to deviate from their fundamentals, leading to extreme peaks and valleys. What tends to go missing from the discussion, though, is that reflexivity can be measured.
To use more precise language, the distributional impact of reflexivity can be identified and thus exploited for trading purposes — assuming, of course, that there is a favorable structural arbitrage between the broader market's expectation of outcomes and the likely forward result.
On the surface, such a methodology sounds ambitious. When observing the technical chart of IONQ stock, investors will notice that the security is down about 35% from the close of the Oct. 13 session. Given the steep discount — combined with some of the fantastical potential undergirding the quantum computing industry — many, if not most speculators will be tempted to take a position.
Obviously, it's impossible to tell when any one person is about to make the leap into IONQ stock or not. However, if you were to study the past behaviors of many investors isolated for the specific situation at hand — in this case, extreme bearish pressure — patterns and tendencies would likely emerge.
This is also the reason why I discretize (compress) weekly price candlesticks into up or down weeks and adopt a frequentist framework. Running analysis on a single strand of continuous price data is vulnerable to distortions and one-off aberrations. However, when we view hundreds or thousands of rolling 10-week trials, patterns become visible.
Under a distributional (as opposed to a continuous) lens, these patterns form the basis of probability density.
Calculating Profits Using IONQ Stock's Risk Geometry
Scientifically, the frequentist approach — called sliding-window empirical distribution — aims to amplify the dataset's hidden structure while neutralizing the impact of aberrations. For example, if a company released rare blockbuster earnings, the price action for that week would be unusually large, thus potentially leading to distortive expectations. However, if that one week is part of a distribution of hundreds of weeks, it would have a negligible impact on the overall tendencies.
On the other end, by analyzing a distribution of hundreds of data points, areas of pronounced probability density are significant. That's because over many trials, the data tends to cluster at a certain point more so than others. This is the structure or risk geometry of a publicly traded security.
So, for all the probability theories, behavioral transition sciences and straight-up calculus, my hypothesis is quite straightforward: reveal the risk geometry of IONQ stock and place an options trade accordingly.
Using the above methodology, the forward 10-week returns of IONQ stock can be arranged as a distributional curve, with median outcomes mostly ranging between $49 and $54 (assuming an anchor price of $52.62). Further, price clustering would likely be predominant at roughly $51.40, thus indicating a negative bias.
The above assessment aggregates all trials since IonQ's public market debut. However, we're interested in the current signal, which is the 3-7-D sequence; that is, in the trailing 10 weeks, IONQ stock printed three up weeks and seven down weeks, with an overall downward slope.
Under this setup, the forward 10-week returns shift quite dramatically, with outcomes ranging between $44.90 and $67. Moreover, price clustering would likely be predominant at $53, indicating a slightly bullish bias.
Still, the opportunity is that, under 3-7-D conditions, IONQ's probabilistic mass is densest between $50 and $55. Further, if we treated probability as a physical object, it would lean toward the positive side of the anchor price. Statistically, then, the bulls should have an edge.
Taking A Measured Shot Instead Of A Haymaker
While it's always tempting to go for ultra-high-payout transactions, you also have to play the game smartly. As a general rule of thumb, you should trade with the data and its distributional structures, as they encompass the gazillion elements that make up price discovery.
With that said, I would be looking most closely at the 50/55 bull call spread expiring Jan. 16, 2026. This wager requires two simultaneous transactions: buy the $50 call and sell the $55 call, for a net debit paid of $260 (the most that can be lost).
Should IONQ stock rise through the second-leg strike ($55) at expiration, the maximum profit would be $240, a payout of over 92%. It's possible, though, that depending on market conditions, the payout could rise to triple digits. If so, that would make this trade all the more tempting.
From a risk geometry perspective, probability density between $55 and $60 drops by 70.13%. From $60 to $65, density plunges by nearly 88%. With the above trade featuring a breakeven price of $52.60, the 55/60 spread is effectively buying the premium associated with just the realistic side of the distributional curve — and selling the rest.
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