Chelsea Addison Capital operates a fully automated trading strategy on SPX 0DTE (zero-days-to-expiration) index options. Rather than conventional time-based 0DTE approaches, the system uses a proprietary, AI-developed entry framework that responds dynamically to market volatility and price expansion.
A departure from «set-and-forget» in favor of true market reactivity:
| Adaptive Chain Intelligence | Proprietary algorithms continuously analyze evolving option chain behavior, triggering entries the moment specific structural changes signal opportunity. |
| Multi-Window Execution | The trading day is segmented into multiple execution windows — each with independently calibrated entry criteria, position sizing, and risk parameters tuned to that window’s liquidity and volatility profile. |
| Dynamic Weighting | Capital allocation and risk exposure adapt dynamically to time-of-day, volatility regime, and real-time market conditions — aggressive when conditions favor it, conservative when they don’t. |
| Intraday Agility | The system scans the market at high frequency throughout the session, enabling rapid response to emerging opportunities and immediate risk management. A fundamental departure from static, time-based 0DTE approaches. |
Because every position expires the same day, risk in this strategy lives and dies intraday. It is managed accordingly — continuously, automatically, and without discretion.
Every position carries pre-defined, automatically enforced exit logic. No position relies on a human watching a screen.
Exposure scales with time-of-day, volatility regime, and live market conditions — the system de-risks automatically when its criteria deteriorate.
Spread-based structures with defined maximum loss are used where appropriate to bound tail exposure.
High-frequency scanning across the full session means risk decisions happen in seconds, not minutes — including on fast, high-volatility days.
The strategy was developed on a custom-built backtesting engine designed around one question: does the logic hold up out of sample? Over-optimization is treated as the primary research risk, with strict controls against curve-fitting. The system is not static — its logic is continuously refined as market regimes evolve, under the same testing discipline that produced it.
We do not publish performance information on this website. Qualified parties with an existing relationship with the Manager may request information directly.