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How to Trade the Hidden Geometry Behind MARA Stock
Posted On Dec 12, 2025 by Joshua Enomoto
Among publicly traded enterprises, Mara Holdings(NASDAQ: MARA) may rank among the most frustrating. On the surface, the cryptocurrency miner is aligned with the broader blockchain ecosystem, which has been disrupting traditional financial paradigms. At the same time, the sector's incredible volatility tends to victimize parallel entities, thus sinking MARA stock.
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The carnage has been ugly, plain and simple. Since the start of the year, MARA stock is down more than 29%. Since mid-October, the security has plunged more than 48%. With the cryptocurrency sector under heavy fire following a stratospheric run, it's difficult to see how the blockchain miner can sustainably work its way out of the current rut.
At the same time, the reflexivity of the equities arena could offer a saving grace for MARA stock, especially from an options trading perspective.
A concept popularized by George Soros, reflexivity refers to the thesis that market valuations aren't governed by perfect equilibrium. Instead, collective participants' beliefs about the market influence prices. Not only that, the subsequent price changes influence (or reinforce) these beliefs, creating a feedback loop. As such, this dynamic could cause the valuations to be divorced from underlying fundamentals.
Colloquially speaking, perception can alter reality. This is the ultimate reason why an ultimate formula that predicts future stock prices can never practically be calculated. Once that ultimate knowledge is known, it would influence behavior — and thus whatever predicted edge would get arbitraged out of existence.
Still, what goes missing in the discussion is that the potential influence of reflexivity (instead of the cause) can be calculated. It all begins with a change of framework.
Taking a Step Away from Event-Based Thinking to Distributional Analysis
In practically 99% of cases in the financial media ecosystem, experts assess price or value chronologically. It's the most intuitive framework available because life obviously evolves in a time-wise manner. However, when it comes to analytical methodologies, this framework can easily lead to erroneous assumptions — unless the aberrations that lead to those assumptions are controlled for.
News flash: most experts do not control for the aberrations, which is what introduces flaws to the fundamental and technical approach to the markets.
Under a chronological lens, one-off events — such as the Federal Reserve implementing an aggressively dovish strategy — can easily distort the price action for the affected week. However, if that one week were stacked in a distribution with multiple other weeks, the impact of that Fed cut wouldn't have a material impact on the overall results.
Using a distributional analysis, aberrations are effectively neutralized by the weight of other data points. However, what raises the probability density is volume. If certain price points are elevated more so than others across multiple iterations, that's a structural phenomenon rather than an aberration. By logical deduction, if we place directional wagers, it only makes intuitive sense to target the thresholds (strike prices) that are most likely to be triggered.
That's the "magic" behind distributional frameworks as opposed to chronological: the former is relational while the latter is merely indexical.
To go a bit deeper, a technical chart merely plots where the market value stood as time passes by. It's not really that instructive. However, under a distributional lens, we can see how market value evolves in relation to another metric. It's much more insightful because, if we identify the metric, we can calculate the expected price output.
Of course, to identify a metric necessarily means the underlying concept must be measurable. Therefore, in order to conduct a distributional analysis, you must first take the continuous strand of price or value and break it apart into rolling windows or trials. This way, you have hundreds, if not thousands, of sequences to build a distributional analysis.
Identifying the Risk Geometry of MARA Stock
Using the methodology above, we can take the MARA stock price history and break it down to multiple 10-week sequences. The idea here is that, while observing how MARA evolves from the beginning of Week 1 to the end of Week 10 for one cycle doesn't tell us anything, observing hundreds of these cycles reveals structure.
Running a bespoke algorithm that processes the rolling sequences automatically, the forward 10-week returns of MARA stock can be arranged as a distributional curve, with outcomes ranging roughly between $11.30 and $12.10 (assuming an anchor price of $11.84). Further, price clustering would likely be predominant at $11.68.
The above assessment aggregates all trials since January 2019. However, we're interested in the current quantitative signal, the 3-7-D sequence; that is, in the past 10 weeks, MARA stock printed three up weeks and seven down weeks, with an overall downward slope.
Under this arrangement, the forward 10-week returns shift quite noticeably, ranging between $10.70 and $13.20, with price clustering likely to occur at $12. By plotting the risk geometry of MARA stock, we can see that it's a high-risk, high-reward idea, with a slight bullish bias (since probabilistic mass is heavier on the bull side).
With the information at hand, the most sensible trade may well be the 11/13 bull call spread expiring Feb. 20, 2026. I use the term as a relative expression because crypto-based investments tend not to be sensible from a conservative perspective.
Still, what I like here is that the breakeven price for the above trade is $11.93, which is right where probability density is thickest. Essentially, MARA stock naturally gravitates toward $12 following the flashing of the 3-7-D quant signal.
However, if MARA stock manages to rise to $13, the aforementioned bull spread will generate a payout of 115%. So, assuming that MARA stock plays out according to its probabilistic tendencies, the call spread will likely break even but with a chance to earn a triple-digit payout.
Seeing Through MARA Holding's Noise With Empirical Geometry
For traders willing to step outside the limits of chronological thinking, MARA stock presents a surprisingly coherent setup. Reflexivity creates the behavioral backdrop, but the real edge emerges when price history is reframed through a distributional lens. By neutralizing aberrations and isolating recurring outcomes, we can identify the levels where MARA naturally gravitates and the thresholds where probability density meaningfully thins out.
In this case, the market's own historical geometry suggests that MARA stock tends to cluster around the $12 region following a similar configuration — a level that conveniently aligns with the breakeven on the 11/13 bull call spread. The upside tail remains volatile, but that volatility is exactly what makes the trade compelling: a realistic path to break even, paired with a structurally supported chance at a triple-digit payout if MARA pushes toward the higher end of the distribution.
Ultimately, the point isn't to forecast the future. It's to position trades where reality is most likely to concentrate. By grounding decisions in empirical risk geometry rather than reactive narratives, traders gain a clear advantage — one rooted not in speculation, but in structure.
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