factor_agent.scoring

Scoring: how a factor’s raw values become the values that are judged.

One setting, shared by the Evaluator and Acceptance, so what is admitted is what is validated and exported. A factor is

1. ranked across the whole market each day: the graph factors rank their own outputs (exported.ranked_function), so the rank is in the compiled graph and an exported factor computes it;

2. neutralised, when the config asks for it, against the industry code and the logarithm of the market cap of the configured exposures and z-scored (quantlab’s NeutralizedFactor), or left as ranked;

3. kept on the members of each day t (IndexConstituentDataset.mask), or on every symbol when there is no membership.

Steps 1 and 2 give the whole-market values a store holds (apply); step 3 is how they, and any stored reference or baseline factor, are read (on_members, read, mask). read takes a reference or known factor given as a component through steps 2 and 3, and one given as a store through step 3 alone. A stored factor is read from its store’s first bar on: it has no value, so no score, before.

Classes

Neutralization	What a ranked factor is neutralised against.
Scoring	Score factors one way; see the module docstring.