Cboe’s new Bitcoin and Ether continuous futures are designed to look and feel like perpetuals, but they live inside a traditional futures stack. The contracts combine a long-dated expiry with daily cash adjustments, delivering persistent exposure without the constant roll overhead.
From a quant and engineering angle, that design raises a few implementation questions:
Pricing & Funding Logic
Each contract tracks a reference index and applies a daily “funding-style” adjustment as a cash flow. In internal systems, that is essentially a scheduled PnL event driven by notional, rate, and time step, not just mark-to-market.
Risk & Margin Models
Because these are long-dated but funded daily, a risk engine should treat them as a hybrid: term risk similar to far-dated futures, short-horizon PnL behavior closer to a perp with discrete funding. Stress tests should include spot gaps and funding shocks, especially for leveraged books.
Cross-Venue Arbitrage
For multi-venue strategies spanning offshore perps and regulated futures, this adds a new leg that behaves like a perp but trades on a different schedule with different margin rules. Session gaps, margin offsets and funding patterns all matter as much as raw spreads.
Data Engineering
Clean time series are essential for:
Daily funding adjustments
Margin requirement changes
Cross-margin offsets with other listed crypto futures
That data underpins backtests, VaR, and real-time dashboards when these contracts go live in production environments.
For teams building execution algos, risk tools or portfolio platforms, the key is to avoid treating continuous futures as “just another front-month.” Their mechanics justify a dedicated schema and a distinct playbook inside the infrastructure.
More insights: https://www.tznxg.com/
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