public LiborForwardModel(LiborForwardModelProcess process,
LmVolatilityModel volaModel,
LmCorrelationModel corrModel)
: base(volaModel.parameters().Count() + corrModel.parameters().Count())
{
f_ = new InitializedList<double>(process.size());
accrualPeriod_ = new InitializedList<double>(process.size());
covarProxy_=new LfmCovarianceProxy(volaModel, corrModel);
process_=process;
/*copy(volaModel.parameters().begin(), volaModel.parameters().end(),
arguments_.begin());
copy(corrModel.parameters().begin(), corrModel.parameters().end(),
arguments_.begin()+k);*/
int k=volaModel.parameters().Count;
for (int j = 0; j < k; j++)
arguments_[j] = volaModel.parameters()[j];
for (int j = 0; j < corrModel.parameters().Count; j++)
arguments_[j+k] = corrModel.parameters()[j];
for (int i=0; i < process.size(); ++i) {
accrualPeriod_[i] = process.accrualEndTimes()[i]
- process.accrualStartTimes()[i];
f_[i] = 1.0/(1.0+accrualPeriod_[i]*process_.initialValues()[i]);
}
}
public VarProxy_Helper(LfmCovarianceProxy proxy, int i, int j)
{
i_=i;
j_=j;
volaModel_=proxy.volaModel_;
corrModel_=proxy.corrModel_;
}
public void testSimpleCovarianceModels()
{
//"Testing simple covariance models...";
//SavedSettings backup;
const int size = 10;
const double tolerance = 1e-14;
int i;
LmCorrelationModel corrModel=new LmExponentialCorrelationModel(size, 0.1);
Matrix recon = corrModel.correlation(0.0,null)
- corrModel.pseudoSqrt(0.0,null)*Matrix.transpose(corrModel.pseudoSqrt(0.0,null));
for (i=0; i<size; ++i) {
for (int j=0; j<size; ++j) {
if (Math.Abs(recon[i,j]) > tolerance)
Assert.Fail("Failed to reproduce correlation matrix"
+ "\n calculated: " + recon[i,j]
+ "\n expected: " + 0);
}
}
List<double> fixingTimes=new InitializedList<double>(size);
for (i=0; i<size; ++i) {
fixingTimes[i] = 0.5*i;
}
const double a=0.2;
const double b=0.1;
const double c=2.1;
const double d=0.3;
LmVolatilityModel volaModel=new LmLinearExponentialVolatilityModel(fixingTimes, a, b, c, d);
LfmCovarianceProxy covarProxy=new LfmCovarianceProxy(volaModel, corrModel);
LiborForwardModelProcess process=new LiborForwardModelProcess(size, makeIndex());
LiborForwardModel liborModel=new LiborForwardModel(process, volaModel, corrModel);
for (double t=0; t<4.6; t+=0.31) {
recon = covarProxy.covariance(t,null)
- covarProxy.diffusion(t,null)*Matrix.transpose(covarProxy.diffusion(t,null));
for (int k=0; k<size; ++k) {
for (int j=0; j<size; ++j) {
if (Math.Abs(recon[k,j]) > tolerance)
Assert.Fail("Failed to reproduce correlation matrix"
+ "\n calculated: " + recon[k,j]
+ "\n expected: " + 0);
}
}
Vector volatility = volaModel.volatility(t,null);
for (int k=0; k<size; ++k) {
double expected = 0;
if (k>2*t) {
double T = fixingTimes[k];
expected=(a*(T-t)+d)*Math.Exp(-b*(T-t)) + c;
}
if (Math.Abs(expected - volatility[k]) > tolerance)
Assert.Fail("Failed to reproduce volatities"
+ "\n calculated: " + volatility[k]
+ "\n expected: " + expected);
}
}
}
