Dual Edge Research publishes two powerful newsletters that work great individually — and even better together. The Bull Strangle Newsletter focuses on stocks and options, combining stock ownership with premium-selling strategies to generate consistent income and market-beating returns. The Smart Spreads Newsletter specializes in seasonal commodity futures spreads, offering a diversified approach with low correlation to equities. Together, they deliver a complete investment perspective — one focused on income, the other on diversification — all under one simple subscription.
Introduction
Over the past several weeks, I’ve been engaged in a detailed review of historical seasonal futures spread data with a very specific objective: to refine how entry and exit decisions should be made before a trade is ever placed. The analysis examined nearly two thousand historical trades across multiple commodity groups and market environments, using modern analytical tools—including AI-assisted data processing—to efficiently identify patterns while keeping interpretation grounded in market structure.
The dataset used in this work comprises seasonal calendar spread trades spanning June 2013 to the present. Each trade is entered and exited strictly according to predefined seasonal dates. There are no stop losses, no profit targets, and no discretionary adjustments of any kind. Trades are allowed to express their natural price behavior from entry to exit fully. That lack of management is not a limitation—it is the point.
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Before discussing refinement, it’s important to establish a baseline. Across the full sample, these unmanaged seasonal spread trades are consistently profitable. The profitability is not confined to a narrow time window, a single commodity group, or a small number of outlier trades. Instead, the edge appears broadly distributed across markets and over time. Equally important, the results exhibit attractive long-term expectancy without reliance on optimization. This is raw seasonality at work—unfiltered and unassisted. However, profitability alone does not tell the full story.
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While the aggregate results are strong, the experience of holding these trades varies dramatically. Some positions progress steadily toward profit with minimal adverse movement. Others ultimately resolve profitably, but only after experiencing significant drawdowns along the way. In still other cases, early adverse movement never meaningfully recovers. These differences are not random. They are strongly linked to the structure of trades and their evolution over time.
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This is where volatility enters the discussion—not as a margin statistic or a historical variance calculation, but as a behavioral characteristic of the trade itself. Understanding how volatility manifests structurally is essential for explaining why some profitable trades are efficient, while others are stressful, capital-intensive, or difficult to hold. To make sense of those differences, volatility must first be defined in a way that reflects how calendar spreads behave in practice once they are live.
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A Structural Definition of Volatility
Once profitability is established as a baseline, the next question becomes more subtle but far more important: Why do some profitable trades feel dramatically different from others while they are live?
In most trading contexts, volatility is defined statistically—through historical variance, implied volatility, or margin requirements. While useful for risk control, those measures do not adequately explain how calendar spreads behave over the holding period. Margin reflects a clearinghouse’s estimate of short-term worst-case risk. It exists to protect the financial system, not to describe the experience of holding a trade or the path by which profits and losses unfold.
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For that reason, volatility in this analysis is defined structurally rather than statistically. The objective is not to measure how much prices can move, but how trades are likely to move over time once entered. Two time-based characteristics consistently account for most behavioral differences observed in the dataset.
Time From Entry to Front-Month Expiration - This measures the time required for the trade to work before the front-month contract expires. Shorter windows compress price discovery. When little time remains, spreads tend to resolve quickly—but often violently. Favorable outcomes may arrive sooner, but adverse movements are magnified, and patience is rarely rewarded. Longer windows, by contrast, allow seasonal forces and relative fundamentals to express themselves gradually. Price paths tend to be smoother, though profits may take longer to materialize.
Time Between the Front and Deferred Contracts - This measures the distance between the two legs of the spread on the futures curve. Wider spacing introduces additional uncertainty as the curve evolves and re-prices. Narrower spacing tends to anchor the relationship more tightly, producing steadier relative movement. Together, these two dimensions define the trade's operating environment.
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Volatility Regimes - Using these characteristics, trades naturally fall into three broad regimes:
High Volatility Trades - Short time to expiration combined with wide contract spacing. These trades often resolve quickly but frequently experience large adverse excursions first. Precision matters; tolerance for drawdowns is tested early.
Mid Volatility Trades - Trades with moderate time compression or spacing. These setups balance opportunity and risk but still require realistic expectations around interim drawdowns.
Low Volatility Trades - Trades with ample time remaining and tighter spacing. These positions tend to evolve more gradually, with smaller drawdowns and smoother progression toward resolution.
Crucially, this classification is applied before examining profitability or outcomes. It does not rank trades by return; it groups them by expected behavior. Once trades are viewed through this lens, a critical insight emerges:
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Volatility does not determine whether a trade is profitable; it largely determines how stressful achieving that profitability is.
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That observation leads directly to the next question:
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If volatility defines behavior; can drawdowns tell us which trades are structurally sound before profits appear?
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That will be the focus of the next article. From there, the analysis proceeds to examine how profits are distributed across volatility regimes, when favorable movements tend to occur, and whether higher volatility meaningfully improves risk-adjusted outcomes. The series then turns to what the data ultimately suggests matters most: how disciplined trade selection improves results before any management rules are applied, and what thoughtful management adds once the right trades are already in place.
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Where Smart Spreads Fits In
This framework—focused on structure, volatility, and drawdown behavior rather than prediction—forms the analytical foundation of the Smart Spreads Newsletter. Smart Spreads applies these same principles to a live watch list of seasonal futures spreads, emphasizing disciplined trade selection and realistic expectations before trades are ever entered. For readers interested in seeing how this research translates into an ongoing, rules-based process, the newsletter is designed to bridge analysis and execution in real time.
More Information
Now you can get two powerful newsletters — for one simple price!
- For stocks and options, the Bull Strangle Newsletter shows you how to combine stock ownership with dual option selling — a disciplined strategy that has consistently outperformed the S&P 500.
- For commodity futures, the Smart Spreads Newsletter focuses on seasonal commodity spreads — a proven, low-correlation approach that thrives in all types of markets.
Each newsletter is designed to deliver consistent income on its own — but when used together, they create a complete, diversified trading approach that works in any market environment.
Visit BullStrangle.com to subscribe for just $1 for the first month.
For a video overview of the Bull Strangle Newsletter
For a video overview of the Smart Spreads Newsletter
Darren Carlat
Dual Edge Research
(214) 636-3133
DualEdgeResearch@gmail.com
Disclaimer
This information is for informational purposes only and should not be considered as investment advice. Past performance is not indicative of future results, and all investments carry inherent risk. Consult with a financial advisor before making any investment decisions.
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