Documentation

This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

simTermStructs

Simulate term structures for Hull-White one-factor model

Syntax

[ZeroRates,ForwardRates] = simTermStructs(HW1F,nPeriods)
[ZeroRates,ForwardRates] = simTermStructs(___,Name,Value)

Description

example

[ZeroRates,ForwardRates] = simTermStructs(HW1F,nPeriods) rsimulates future zero curve paths using a specified HullWhite1F object.

example

[ZeroRates,ForwardRates] = simTermStructs(___,Name,Value) adds optional name-value pair arguments.

Examples

collapse all

Create a HW1F object.

Settle = datenum('15-Dec-2007');
CurveTimes = [1:5 7 10 20]';
ZeroRates = [.01 .018 .024 .029 .033 .034 .035 .034]';
CurveDates = daysadd(Settle,360*CurveTimes,1);

irdc = IRDataCurve('Zero',Settle,CurveDates,ZeroRates);

alpha = .1;
sigma = .01;
 
HW1F = HullWhite1F(irdc,alpha,sigma)
HW1F = 
  HullWhite1F with properties:

    ZeroCurve: [1x1 IRDataCurve]
        Alpha: @(t,V)inAlpha
        Sigma: @(t,V)inSigma

Simulate the term structures for the specified HW1F object.

SimPaths = simTermStructs(HW1F, 10,'nTrials',100);

Input Arguments

collapse all

HullWhite1F object, specified using the HW1F object created using HullWhite1F.

Data Types: object

Number of simulation periods, specified as a numeric value. For example, to simulate 12 years with an annual spacing. specify 12 as the nPeriods input and 1 as the optional deltaTime input (note that the default value for deltaTime is 1).

Data Types: double

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: [ZeroRates,ForwardRates] = simTermStructs(HW1F,NPeriods,'nTrials',100,'deltaTime',dt)

collapse all

Time step between nPeriods measured in years, specified as a scalar numeric value. For example, to simulate 12 years with an annual spacing. specify 12 as the nPeriods input and 1 as the optional deltaTime input (note that the default value for deltaTime is 1).

Data Types: double

Number of simulated trials (sample paths), specified as a positive scalar integer value of nPeriods observations each. If you do not specify a value for this argument, the default is 1, indicating a single path of correlated state variables.

Data Types: double

Flag indicating whether antithetic sampling is used to generate the Gaussian random variates that drive the zero-drift, unit-variance rate Brownian vector dW(t), specified as a Boolean scalar flag. For details, see simBySolution.

Data Types: logical

Direct specification of the dependent random noise process, specified as a numeric value. The Z value is used to generate the zero-drift, unit-variance rate Brownian vector dW(t) that drives the simulation. For details, see simBySolution for the HWV model. If you do not specify a value for Z, simBySolution generates Gaussian variates.

Data Types: double

Maturities to compute at each time step, specified as a numeric vector.

Tenor enables you to choose a different set of rates to output than the underlying rates. For example, you may want to simulate quarterly data but only report annual rates; this can be done by specifying the optional input Tenor.

Data Types: double

Output Arguments

collapse all

Simulated zero-rate term structures, returned as a nPeriods+1-by-nTenors-by-nTrials matrix.

Simulated zero-rate term structures, returned as a nPeriods+1-by-nTenors-by-nTrials matrix. The ForwardRates output is computed using the simulated short rates and by using the model definition to recover the entire yield curve at each simulation date.

Introduced in R2013a

Was this topic helpful?