yieldcurveml.interpolatecurve

 27class CurveInterpolator(RateCurveBootstrapper, CurveStripper):
 28    """Yield curve interpolator.
 29    
 30    Parameters
 31    ----------
 32    estimator : sklearn estimator, default=None
 33        Scikit-learn estimator to use for fitting. If None, uses Ridge.
 34    lambda1 : float, default=2.5
 35        First lambda parameter for NSS function
 36    lambda2 : float, default=4.5
 37        Second lambda parameter for NSS function
 38    type_regressors : str, default="laguerre"
 39        Type of basis functions, one of "laguerre", "cubic"
 40    """
 41    def __init__(
 42        self,
 43        estimator=None,
 44        lambda1: float = 2.5,
 45        lambda2: float = 4.5,
 46        type_regressors: Optional[Literal["laguerre", "cubic", "kernel"]] = "cubic",
 47        kernel_type: Optional[Literal['matern', 'rbf', 'rationalquadratic', 'smithwilson']] = None,
 48        interpolation: Literal['linear', 'cubic'] = 'linear',
 49        **kwargs
 50    ):
 51        self.estimator = estimator
 52        self.lambda1 = lambda1
 53        self.lambda2 = lambda2
 54        self.type_regressors = type_regressors
 55        self.kernel_type = kernel_type
 56        self.interpolation = interpolation
 57        self.maturities = None
 58        if self.type_regressors != "kernel":
 59            self.kernel_type = None
 60        self.maturities = None
 61        self.swap_rates = None
 62        self.tenor_swaps = None
 63        self.T_UFR = None
 64        self.kernel_params_ = kwargs  # Store kernel parameters
 65        self.coef_ = None
 66        self.cashflows_ = None
 67        self.maturities = None
 68        self.curve_rates_ = None
 69
 70    def fit(
 71        self, 
 72        maturities: np.ndarray, 
 73        yields: np.ndarray,
 74        T_UFR: Optional[float] = None,
 75        **kwargs
 76    ) -> "CurveInterpolator":
 77        """Fit the curve Interpolator model.
 78        
 79        Parameters
 80        ----------
 81        maturities : np.ndarray
 82            Maturities of the swap rates
 83        yields: np.ndarray
 84            Yields to interpolate
 85        T_UFR : float, default=None
 86            UFR to use for the Smith-Wilson method
 87
 88        Returns
 89        -------
 90        self : CurveInterpolator
 91            Fitted curve Interpolator model
 92        """
 93        assert len(maturities) == len(yields), "Maturities and yields must have the same length"
 94        self.maturities = np.asarray(maturities)
 95        self.yields = np.asarray(yields)
 96        self.T_UFR = T_UFR        
 97        # Store inputs
 98        self.rates_ = YieldsContainer(maturities=self.maturities, yields=self.yields)        
 99        # Calculate discount factors from actual yields
100        V = np.exp(-self.maturities * self.yields)
101        # Get basis functions
102        X = self._get_basis_functions(self.maturities)
103        if X.ndim == 1:
104            X = X.reshape(-1, 1)
105        # Use actual discount factors to calculate target values
106        y = (1 - V) / self.maturities
107        # Fit the model
108        self.estimator.fit(X=X, y=y, **kwargs)
109        predictions = self.estimator.predict(X)
110        self.residuals_ = predictions - y
111        return self
112
113    def predict(self, maturities: np.ndarray) -> np.ndarray:
114        """Predict interpolated rates at given maturities."""
115        check_is_fitted(self)
116        X = self._get_basis_functions(maturities)
117        if X.ndim == 1:
118            X = X.reshape(-1, 1)        
119        # Model predicts (1-V)/T values
120        y_pred = self.estimator.predict(X)        
121        # Convert back to spot rates
122        spot_rates = -np.log(1 - y_pred * maturities) / maturities
123        discount_factors = np.exp(-maturities * spot_rates)
124        forward_rates = self._calculate_forward_rates(maturities, spot_rates, discount_factors)
125        
126        return CurveRates(
127            maturities=maturities,
128            spot_rates=spot_rates,
129            forward_rates=forward_rates,
130            discount_factors=discount_factors
131        )