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Financial Machine Learning / Importance, calibration and sizing

Regime features

The event classifier's probabilities were sized under a reference population. A later market can change the features, the mapping from features to outcomes, or the costs that turn a correct side into a loss. This note decides which of those changes the researcher is allowed to call a regime feature, using only the distinctions already in drift, decay and retirement and the drawdown discussion in portfolio risk and the quant quake. It does not introduce a structural-break test.
Learning objectives. By the end of this note you should be able to:
  • separate feature drift, relationship change and economic decay for the event book;
  • refuse a drawdown print as proof that the classifier's conditional model broke;
  • name one feature-distribution check and one economics check that the promotion notes already justify;
  • write a regime ticket that freezes what would falsify continued sizing.

In this lesson

  1. Three changes, three responses
  2. A drawdown is an operating rule
  3. The regime ticket

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