voiage.methods.dynamic_real_options.value_of_flexibility

value_of_flexibility

value_of_flexibility([positional or keyword] net_benefits: np.ndarray = None, [positional or keyword] decision_stage_names: Sequence[str] = None, [positional or keyword] strategy_names: Sequence[str] = None, [positional or keyword] stage_weights: Mapping[str, float] = None, [positional or keyword] provenance: Mapping[str, str] = None, [positional or keyword] discount_rate: float = 0.0, [positional or keyword] irreversibility_penalty: float = 0.0, [positional or keyword] lock_in_penalty: float = 0.0, [positional or keyword] evidence_arrival_times: Mapping[str, float] | None = None, [keyword-only] flexible_policy_sets: Mapping[str, Sequence[str]] | None = None, [keyword-only] constrained_strategy_names: Sequence[str] | None = None, [keyword-only] value_unit: str = 'value-unit', [keyword-only] stage_semantics: str = 'timing_scenarios', [keyword-only] information_value_included: bool = False) -> ValueOfFlexibilityResult

Value scenario-contingent flexibility against ex-ante commitment.

This experimental v1 estimator treats stages as mutually exclusive timing scenarios. It does not accept lifecycle-period aggregation or an embedded information-value component.

Parameters:

• net_benefits np.ndarray
• decision_stage_names Sequence[str]
• strategy_names Sequence[str]
• stage_weights Mapping[str, float]
• provenance Mapping[str, str]
• discount_rate float (default: 0.0)
• irreversibility_penalty float (default: 0.0)
• lock_in_penalty float (default: 0.0)
• evidence_arrival_times Mapping[str, float] | None (default: None)
• flexible_policy_sets Mapping[str, Sequence[str]] | None (default: None)
• constrained_strategy_names Sequence[str] | None (default: None)
• value_unit str (default: 'value-unit')
• stage_semantics str (default: 'timing_scenarios')
• information_value_included bool (default: False)

Returns: ValueOfFlexibilityResult