finpricing.model.bond_curve_solver

Module Contents

Classes

BondCurveAnalyticsHelper
PenaltyParameter
BondCurveSolver

class finpricing.model.bond_curve_solver.BondCurveAnalyticsHelper(bonds)

property recovery_rates

property dirty_prices

property discount_curves

property survival_curves

property settlement_dates

property valuation_date

property maturity_dates

maturity dates of all bonds in the portfolio

property maturity_span

maximum maturity minus minimum maturity in years

setup(valuation_date: datetime.date | finpricing.utils.date.Date = None, dirty_prices: List[float] = None, discount_curves=None, survival_curves=None, recovery_rates=None, settlement_dates=None)

setup the helper in one go

get_bond_bases(valuation_date: datetime.date | finpricing.utils.date.Date = None, dirty_prices: List[float] = None, survival_curves=None, basis_type: str = 'AdditiveZeroRates')

class finpricing.model.bond_curve_solver.PenaltyParameter

penalty_ridge_tuning: float = 0.0001

penalize_sample_size: bool = True

penalize_maturity_span: bool = True

penalize_inverted_curve: bool = True

penalty_inverted_tuning: float = 0.2

penalty_inverted_threshold: float = 0.01

median_dummy_curve_level: float = 0.009730434692816878

class finpricing.model.bond_curve_solver.BondCurveSolver(bondAnalyticsHelper: BondCurveAnalyticsHelper, initial_params=None, weights=None, penalty_params: PenaltyParameter = None)

getSurvivalCurveGenerator(bondAnalyticsHelper: BondCurveAnalyticsHelper)

return a survival curve generator that can generate survival curves from parameters

This is actually not a true generator, but a survival curve that has the method to recreate a new survival curve with the same anchor date and pivot dates but different parameters.

get_euqal_weights()

return a list of equal weights for all bonds

static welsch_loss(x)

get_penalty(params: List[float])

_get_tuning_scalar()

_get_hazard_rate_derivative_at_zero(params: List[float])

solve(dirty_prices: List[float] = None, weights: List[float] = None, params: List[float] = None)

solve the best parameters for the survival curve that minimizes the weighted residuals

get_weighted_residuals_and_penalty(params: List[float], dirty_prices: List[float], weights: List[float], valuation_date: datetime.date | finpricing.utils.date.Date = None, basis_type: str = 'AdditiveZeroRates')