Dated contracts first
We preserve the identity of the actual delivery months instead of hiding the research behind an opaque continuous series.
We built FuturesSpread to turn dated futures contracts, seasonal relationships and curve structure into research that traders can actually inspect — not black-box scores they are expected to trust.
Seasonality can look convincing in a single average line. But averages can hide weak years, unstable regimes and extreme outliers. FuturesSpread is designed so every headline statistic can be traced back to the contracts and historical seasons behind it.
We preserve the identity of the actual delivery months instead of hiding the research behind an opaque continuous series.
Average, median, win rate, drawdown, individual years and selected-window P&L are visible together.
Seasonality, contango, backwardation and curve structure are research context — not automatic predictions.
Discovery, validation, curve context and historical evidence belong in one coherent workspace.
Our historical foundation is built around Bloomberg data and contract-level mappings. The goal is simple: when a spread says July minus December, the history should represent that same economic relationship year after year.
We want the speed and polish of a modern SaaS product without sacrificing the ability to inspect the raw historical logic behind the result.
Open the product and test a spread yourself.
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