Market Regime
The volatility methodology evaluates strategy behavior across various market environments and transitions. The system categorizes historical conditions into specific states, such as high volatility, chop, sideways, bear, and trend. The analysis isolates specific conditions to show how a strategy's logic interacts with safety mechanisms during persistent environments, such as a high volatility to high volatility regime, or during shifts, such as a trend transitioning to high volatility.
Historical Pattern
Historical scenarios reveal specific failure modes and system responses across different populations. In a persistent high volatility regime, populations of 5301 and 9943 historical data points showed a dominant failure mode of excessive drawdown. In these instances, the rescue share was 1.0, indicating that all identified failures were addressed by the system's rescue logic. The mean counterfactual distance, which measures proximity to a simulated failure boundary, was recorded at 0.8625 and 1.8436 for these high volatility populations. Other observed transitions include a chop to chop environment with a population of 9280 and a mean counterfactual distance of 2.1495, and a trend to high volatility shift with a population of 6295 and a distance of 2.7714. Across these evaluated populations, the rescue share remained 1.0.
Workflow Pointer
Use this methodology to understand a strategy's proximity to historical failure points under specific market conditions. The surface visualizes how much a parameter would need to change to alter the outcome and quantifies the average magnitude of adjustments across the population. This view isolates specific regime changes to highlight sensitivity and historical performance patterns. This analysis provides a quantitative measure of stress on the parameters but does not predict future outcomes, as market conditions can change rapidly.