Market Regime
Market regimes describe the prevailing environmental conditions of an asset class over a specific period. The analysis categorizes these environments into distinct states, such as "chop," "sideways," "crisis," "bear," "high_vol," and "trend". Understanding these definitions is critical for evaluating how a system transitions between states, such as moving from a crisis regime directly into another crisis regime, or shifting from a sideways trend into a bear market.
Historical Pattern
Historical simulations evaluate how systems perform across thousands of data points within these defined regimes. A key metric observed is the mean counterfactual distance, which measures the average magnitude of parameter adjustment needed to alter an outcome or avoid a dominant failure mode, such as excessive drawdown. For example, a rescue share of 1.0 indicates that a parameter adjustment existed within the dataset that could have prevented the failure in the observed scenarios. These historical patterns illustrate sensitivity near specific regime boundaries, though they are historical simulations and not predictions of future performance.
Workflow Pointer
Use this view to understand system behavior and sensitivity during specific, sustained market conditions or transitions. This information provides context for robustness analysis when evaluating different market shifts. To explore further, review the detailed report or generate a new surface with different assumptions.