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Today's editorial pick for you
This High-Risk ENB Stock Quant Trade is Surprisingly Rational
Posted On Dec 19, 2025 by Joshua Enomoto
While energy infrastructure investments like Enbridge(NYSE:ENB) offer extensive relevance, they're by no means risk-free. For example, ENB stock attracts market participants thanks to its robust yield, which currently stands at around 5.95%. With the Federal Reserve cutting the benchmark interest rate multiple times this year, high-dividend-paying companies tend to look more enticing. Still, that's not the only story here.
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True, ENB stock has gained over 10% on a year-to-date basis. Tack on the dividend yield, and the net return is slightly better than the 15.19% performance of the S&P 500 index during the same frame. However, in the past six months, ENB has moved by less than 4%. In contrast, the benchmark equities index has gained over 13%.
Put differently, the broader market is gaining momentum, even as it digests the latest headwinds, such as concerns of a bubble brewing in artificial intelligence. On the other hand, ENB stock, which effectively serves as a proxy for real-time economic demand, has struggled. That's not a great sign for those who have a macro view of market sentiment.
Still, on a micro level, the downturn in ENB stock presents a potential opportunity. Basically, we know that the financial market — specifically the phenomenon of price discovery — is reflexive. While it's difficult to say with certainty what the source of reflexivity actually is, we can measure its impact.
Utilizing a New Framework to Understand the Market
At the core, trading is a multi-dimensional discipline. While this point may sound obvious, it's also where so many individual traders get tripped up. Indeed, one of the questions that always comes up in trading-focused financial publications is where will the target stock go?
It's a completely understandable question — and it also happens to be the wrong one.
First, there has never been a proven, reliable system or machine for predicting stock prices. That's not a controversial opinion; it's simply a structural fact of how markets work. Essentially, as adaptive environments, it's impossible for such a system to ever materialize without being arbitraged out of existence or tightly controlled and rendered invisible to the public.
Second, deterministic outlooks are mathematically incoherent as linearity is effectively integrated into the formulation, at least at the local level. That's because determinism follows the "if X, then Y" logical structure. It's a cause-and-effect relationship, which is quite dangerous to make in the market because price discovery is non-linear.
Plus, deterministic forecasts from finance folks — who are typically not mathematically trained — are subject to serious credibility concerns. Equity valuations and the reflexivity that undergird them involve complex heteroskedasticity and non-ergodic dynamics. Even the most brilliant astrophysicists would struggle to craft a deterministic forecasting system.
Structurally, then, the best that we can hope for is a probabilistic system. Rather than attempting to guess where a stock will go, our job is to find where it tends to stop going. That's transitional logic, and it can only come from fixed-time distributional analysis.
If we took a single 10-week cycle of ENB stock, the return during this period won't tell us much about what to expect for the other cycles in the dataset. But if we stacked hundreds of 10-week trials or sequences in a fixed-time distribution, the most consistent performance metrics would create a bulge in probability density.
This bulge represents risk geometry; that is, we know where ENB stock would likely gravitate toward — and where that gravitational pull starts to weaken.
Using Distributional Analysis to Trade ENB Stock
Since January 2019, the 10-week returns of ENB stock would form a distributional curve, with median outcomes ranging mostly between $46.60 and $47.80 (assuming an anchor price of $46.74). Further, price clustering would likely occur around $47.25, indicating a slight bullish bias.
However, we're interested in isolating for the current quantitative sequence, which is the 4-6-D formation; that is, in the trailing 10 weeks, ENB stock printed only four up weeks, leading to an overall downward slope.
Usually, a balance of trades where the bears outnumber the bulls is problematic. Statistically, though, when the 4-6-D sequence flashes, ENB stock tends to swing higher — perhaps due to the reflexive response of the market.
If the same contrarian response were to hold true, bullish traders would be looking at a distributional range between $46.50 and $49.50. Moreover, price clustering would occur just shy of $48.50.
Interestingly, probability density falls off a cliff past the aforementioned mark, which effectively means that bullish traders have a limited window to speculate. There's a reason why asking where ENB stock will go over a given period of time is the wrong question: the follow-up to any answer would be why not any higher or lower?
Stated differently, it's a waste of money to gamble on the debit side of a long trade if the underlying premium encompasses price outlooks that have little chance of materializing. A much shrewder idea would be to buy the debit of the outlook you believe is credible — and sell the part of the distribution that is not.
Follow the Data
With the market intelligence above, the seemingly risky 47.50/50 bull call spread expiring Feb. 20, 2026, may actually be sensible. Sure, the $50 strike price is going to be extremely difficult to reach. However, the breakeven price lands at $48.55, which is almost right on the peak of probabilistic mass.
While terribly aggressive, this structure allows speculators to anchor the bull spread on a stable stud. From there, they can play for the $50 strike, where triggering the lofty level at expiration would lead to a payout of over 138%.
Of course, it must be stressed that the chances of this trade being fully profitable are quite low. However, a strong surge should allow this spread to be attractive because you're not paying for an outcome that is completely unrealistic. That's why calculating risk geometry is vital. It's not just about attempting to make good decisions but also limiting the impact of bad ones.
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