com.opengamma.strata.math.impl.interpolation

Class SmithWilsonCurveFunction

java.lang.Object

com.opengamma.strata.math.impl.interpolation.SmithWilsonCurveFunction

public class SmithWilsonCurveFunction
extends Object

Smith-Wilson curve function.

The curve represents the discount factor values as a function of time.

The curve is controlled by omega, alpha and weights: omega is related to the ultimate forward rate (UFR) by omega = log(1 + UFR), the alpha parameter determines the rate of convergence to the UFR, and the weights are the parameters to be calibrated to market data.

Field Summary

Fields

Modifier and Type	Field and Description
static SmithWilsonCurveFunction	DEFAULT Default implementation with UFR = 4.2%

Method Summary

Modifier and Type	Method and Description
double	firstDerivative(double x, double alpha, DoubleArray nodes, DoubleArray weights) Computes the gradient of the Smith-Wilson curve function at a x value.
static double	gap(double x, double alpha, DoubleArray nodes, DoubleArray weights) Computes the gap from the UFR at x value.
static SmithWilsonCurveFunction	of(double ufr) Creates an instance with UFR.
DoubleArray	parameterSensitivity(double x, double alpha, DoubleArray nodes) Computes the sensitivity of the Smith-Wilson curve function to weights parameters at a x value.
double	value(double x, double alpha, DoubleArray nodes, DoubleArray weights) Evaluates the Smith-Wilson curve function at a x value.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

DEFAULT

public static final SmithWilsonCurveFunction DEFAULT

Default implementation with UFR = 4.2%

Method Detail

of

public static SmithWilsonCurveFunction of(double ufr)

Creates an instance with UFR.

Parameters:

ufr - the UFR

Returns:

the instance

gap

public static double gap(double x,
                         double alpha,
                         DoubleArray nodes,
                         DoubleArray weights)

Computes the gap from the UFR at x value.

The nodes must be sorted in ascending order and coherent to weights.

Parameters:

x - the x value

alpha - the alpha parameter

nodes - the nodes

weights - the weights

Returns:

the gap

value

public double value(double x,
                    double alpha,
                    DoubleArray nodes,
                    DoubleArray weights)

Evaluates the Smith-Wilson curve function at a x value.

The nodes must be sorted in ascending order and coherent to weights.

Parameters:

x - the x value

alpha - the alpha parameter

nodes - the nodes

weights - the weights

Returns:

the value

firstDerivative

public double firstDerivative(double x,
                              double alpha,
                              DoubleArray nodes,
                              DoubleArray weights)

Computes the gradient of the Smith-Wilson curve function at a x value.

The nodes must be sorted in ascending order and coherent to weights.

Parameters:

x - the x value

alpha - the alpha parameter

nodes - the nodes

weights - the weights

Returns:

the gradient

parameterSensitivity

public DoubleArray parameterSensitivity(double x,
                                        double alpha,
                                        DoubleArray nodes)

Computes the sensitivity of the Smith-Wilson curve function to weights parameters at a x value.

The nodes must be sorted in ascending order.

Parameters:

x - the x value

alpha - the alpha parameter

nodes - the nodes

Returns:

the value