factor_agent.web.run_view.Factor

class Factor(label, round, slot, mechanism_type, hypothesis, description, code, factor_direction, ic_mean, ic_t, partial_ic_mean, partial_ic_t, threshold, threshold_source, monotonicity, nearest, nearest_known, decile_returns, coverage, metrics, intraday=False)

Bases: object

An accepted factor, written up with the facts that say how far to trust it.

label is the name the Evaluator and Acceptance give it, "<description> (accepted in round N)". round, slot and mechanism_type place it in the run; hypothesis, description and code are its candidate’s. factor_direction is +1 when a higher value went with a higher training return, -1 when with a lower one. ic_mean, ic_t, partial_ic_mean and partial_ic_t are the training IC and the partial IC and their Newey-West t, in the factor’s direction, as admission judged them; metrics holds every statistic as the ledger records it, the raw values among them. threshold is its round’s t threshold and threshold_source where it comes from: "admission" (the admission events of its round), "refusals" (what its round’s refusals quote, for a run without events) or "carried_over" (neither gives it, so it is an earlier round’s); both are None while nothing gives a threshold. decile_returns and coverage are the Evaluator’s. intraday is its trial’s (Trial.intraday): its graph holds a session aggregation.

Attributes

Factor.intraday = False

Factor.label

Factor.round

Factor.slot

Factor.mechanism_type

Factor.hypothesis

Factor.description

Factor.code

Factor.factor_direction

Factor.ic_mean

Factor.ic_t

Factor.partial_ic_mean

Factor.partial_ic_t

Factor.threshold

Factor.threshold_source

Factor.monotonicity

Factor.nearest

Factor.nearest_known

Factor.decile_returns

Factor.coverage

Factor.metrics