cds basket

financepy.products.credit.cds_basket

Class

CDSBasket

CDSBasket(
    step_in_dt: Date,
    maturity_dt: Date,
    num_credits: int,
    n_to_default: int,
    notional: float = 1000000,
    running_cpn: float = 0.0,
    long_protect: bool = True,
    freq_type: FrequencyTypes = <FrequencyTypes.QUARTERLY: 4>,
    accrual_dc_type: DayCountTypes = <DayCountTypes.ACT_360: 8>,
    cal_type: CalendarTypes | list | tuple = <CalendarTypes.WEEKEND: 2>,
    bd_type: BusDayAdjustTypes = <BusDayAdjustTypes.FOLLOWING: 2>,
    dg_type: DateGenRuleTypes = <DateGenRuleTypes.BACKWARD: 2>,
) -> None

Class to deal with n-to-default CDS baskets.

Methods

value_gaussian_mc


value_gaussian_mc(
    self,
    value_dt: Date,
    issuer_curves: list[financepy.market.curves.cds_curve.CDSCurve],
    corr_matrix: numpy.ndarray,
    num_trials: int,
    seed: int,
    use_moment_matching: bool = False,
    use_sobol: bool = False,
)

Value the default basket using a Gaussian copula model. This depends on the issuer discount and correlation matrix.

value_student_t_mc


value_student_t_mc(
    self,
    value_dt: Date,
    issuer_curves: list[financepy.market.curves.cds_curve.CDSCurve],
    corr_matrix: numpy.ndarray,
    degrees_of_freedom: int,
    num_trials: int,
    seed: int,
    use_moment_matching: bool = False,
    use_sobol: bool = False,
)

Value the default basket using the Student-T copula.

value_1f_gaussian_homo


value_1f_gaussian_homo(
    self,
    value_dt: Date,
    issuer_curves: list[financepy.market.curves.cds_curve.CDSCurve],
    beta_vector: numpy.ndarray,
    num_points: int = 25,
)

Value default basket using 1 factor Gaussian copula and analytical approach which is only exact when all recovery rates are the same.

value_legs_mc


value_legs_mc(
    self,
    value_dt: Date,
    default_times: numpy.ndarray,
    issuer_curves: list[financepy.market.curves.cds_curve.CDSCurve],
)

Vectorised MC valuation of n-to-default basket legs.

spread_dv01s


spread_dv01s(
    self,
    value_dt,
    issuer_curves,
    beta_vector,
)

No description available.

Generated automatically from the FinancePy source code. Do not edit this file manually.