Building this required working from years of historical options trade data, which is usable but not as clean as full quote-level history. Because some contracts can be sparse on certain days, the process had to be filtered carefully so that contracts with unavailable or unusable trade data, zero volume, too few transactions, bad pricing, invalid expiry structure, or unstable delta estimates were excluded from the decision set. To keep the backtest realistic, I applied a 10 bps transaction cost assumption plus 5 bps of slippage off trade price. In practice, that is likely conservative given the data source and the fact that sparse trade prints can make execution look worse than a more complete market snapshot would suggest. Conceptually, the strategy is aimed at a mostly automated options-based system with a proprietary, independently operating risk-aware hedge layer running in parallel. The central question is whether a system like this can outperform common medium-volatility equity exposure on a risk-adjusted basis by using options to create the core directional exposure, while allowing a proprietary risk-on / risk-off stress indicator to dynamically trigger hedge responses when conditions deteriorate. Throughout the backtest, the underlying ETF itself was not bought or sold. The core exposure came from the options structure.
The core idea is to create a more aggressive, options-based equity overlay for investors who still want discipline around capital deployment. The system is designed to participate in slower upward movement while adjusting its premium outlay as portfolio equity changes through time. If account equity falls, the premium budget falls with it. If the account grows, the premium budget grows within fixed sizing logic, implying that after a certain point it does not scale one-for-one in order to help prevent overleveraging during extreme upside periods.