/// <summary>
/// Populate editable fields from name and value vectors
/// specific to the Heston extended process.
/// </summary>
/// <param name="stocProcess">
/// The stochastic process which is being referenced to.
/// </param>
/// <param name="estimate">
/// The estimation result which contains values and names of parameters.
/// It will be searched for S0, kappa, theta, sigma, V0 and rho.
/// </param>
public void Populate(IStochasticProcess stocProcess, EstimationResult estimate)
{
bool found;
this.S0 = new ModelParameter(PopulateHelper.GetValue("S0", estimate.Names, estimate.Values, out found), this.S0.Description);
this.k = new ModelParameter(PopulateHelper.GetValue("kappa", estimate.Names, estimate.Values, out found), this.k.Description);
this.theta = new ModelParameter(PopulateHelper.GetValue("theta", estimate.Names, estimate.Values, out found), this.theta.Description);
this.sigma = new ModelParameter(PopulateHelper.GetValue("sigma", estimate.Names, estimate.Values, out found), this.sigma.Description);
this.V0 = new ModelParameter(PopulateHelper.GetValue("V0", estimate.Names, estimate.Values, out found), this.V0.Description);
int index = stocProcess.NoiseIndex;
ProjectProcess prj = stocProcess.Context as ProjectProcess;
// Update the correlation matrix.
prj.Processes.r.Set(index, index + 1, (RightValue)PopulateHelper.GetValue("rho", estimate.Names, estimate.Values, out found));
bool errors = RetrieveCurve(stocProcess.Context, false);
if (!errors)
{
this.zrCurve.Expr = (estimate.Objects[0] as Matrix).ToArray();
this.dyCurve.Expr = (estimate.Objects[1] as Matrix).ToArray();
//Calibrator assumes dividend yield is a step constant function, the simulation model must be coherent with that assumption.
(this.dyCurve as PFunction).m_Function.iType = DVPLUtils.EInterpolationType.ZERO_ORDER_LEFT;
}
}
public void Populate(IStochasticProcess container, EstimationResult estimate)
{
bool found;
this.s0 = new ModelParameter(PopulateHelper.GetValue("S0", estimate.Names, estimate.Values, out found), this.s0.Description);
bool errors = RetrieveCurve(container.Context, false);
if (!errors)
{
PFunction rFunc = estimate.Objects[0] as PFunction;
PFunction rFuncDest = this.r.fVRef() as PFunction;
rFuncDest.Expr = rFunc.Expr;
PFunction qFunc = estimate.Objects[1] as PFunction;
PFunction qFuncDest = this.q.fVRef() as PFunction;
qFuncDest.Expr = qFunc.Expr;
//Calibrator assumes dividend yield is a step constant function, the simulation model must be coherent with that assumption.
qFuncDest.m_Function.iType = DVPLUtils.EInterpolationType.ZERO_ORDER_LEFT;
PFunction2D.PFunction2D localVolSrc = estimate.Objects[2] as PFunction2D.PFunction2D;
PFunction2D.PFunction2D localVolDest = this.localVol.fVRef() as PFunction2D.PFunction2D;
localVolDest.Expr = localVolSrc.Expr;
localVolDest.Interpolation = localVolSrc.Interpolation;
}
}
/// <summary>
/// Populate editable fields from name and value vectors
/// specific to Pelsser.
/// </summary>
/// <param name="names">
/// An array with the names of the variable,
/// will search for alpha1 (or a), sigma1 (or sigma) and lamba0.
/// </param>
/// <param name="values">The values associated to the parameters in names.</param>
public void Populate(string[] names, double[] values)
{
bool found;
this.a1 = new ModelParameter(PopulateHelper.GetValue("alpha1", "a", names, values, out found), a1Description);
this.sigma1 = new ModelParameter(PopulateHelper.GetValue("sigma1", "sigma", names, values, out found), sigma1Description);
this.lamda0 = new ModelParameter(PopulateHelper.GetValue("lambda0", "lambda", names, values, out found), lambda0Description);
}
private void bgCreateScript_DoWork(object sender, DoWorkEventArgs e)
{
string[] sourceLines = (string[])e.Argument;
PopulateHelper popHelper = new PopulateHelper(null);
string script = popHelper.GeneratePopulateScriptsFromDataExtractFile(sourceLines);
e.Result = script;
}
/*
* /// <summary>
* /// Populate editable fields from name and value vectors
* /// specific to HW.
* /// </summary>
* /// <param name="names">
* /// An array with the names of the variable,
* /// will search for alpha (or a1), sigma (or sigma1).
* /// </param>
* /// <param name="values">The values associated to the parameters in names.</param>
* public void Populate(string[] names, double[] values)
* {
* bool found = false;
* this.alpha1 = new ModelParameter(PopulateHelper.GetValue("alpha", "a1", names, values, out found), alphaDescription);
* this.sigma1 = new ModelParameter(PopulateHelper.GetValue("sigma", "sigma1", names, values, out found), sigmaDescription);
* this.lambda0 = new ModelParameter(PopulateHelper.GetValue("Lambda0", "lambda0", names, values, out found), lambda0Description);
* }
*/
/// <summary>
/// Populate editable fields from name and value vectors
/// specific to the Heston extended process.
/// </summary>
/// <param name="stocProcess">
/// The stochastic process which is being referenced to.
/// </param>
/// <param name="estimate">
/// The estimation result which contains values and names of parameters.
/// It will be searched for S0, kappa, theta, sigma, V0 and rho.
/// </param>
public void Populate(IStochasticProcess stocProcess, EstimationResult estimate)
{
bool found;
this.alpha1 = new ModelParameter(PopulateHelper.GetValue("alpha", "a1", estimate.Names, estimate.Values, out found), alphaDescription);
this.sigma1 = new ModelParameter(PopulateHelper.GetValue("sigma", "sigma1", estimate.Names, estimate.Values, out found), sigmaDescription);
this.lambda0 = new ModelParameter(PopulateHelper.GetValue("Lambda0", "lambda0", estimate.Names, estimate.Values, out found), lambda0Description);
}
public void Populate(string[] names, double[] values)
{
bool found;
this.spot = new ModelParameter(PopulateHelper.GetValue(spotLabel, names, values, out found), spotLabel);
this.mu = new ModelParameter(PopulateHelper.GetValue(muLabel, names, values, out found), muLabel);
this.lambda = new ModelParameter(PopulateHelper.GetValue(lambdaLabel, names, values, out found), lambdaLabel);
this.sigma = new ModelParameter(PopulateHelper.GetValue(sigmaLabel, names, values, out found), sigmaLabel);
}
/// <summary>
/// Populate editable fields from name and value vectors
/// specific to HW2.
/// </summary>
/// <param name="names">
/// An array with the names of the variable,
/// will search for alpha1 (or a1), sigma1 (or sigma), alpha2 (or a2), sigma2 and rho.
/// </param>
/// <param name="values">The values associated to the parameters in names.</param>
public void Populate(string[] names, double[] values)
{
bool found = false;
this._a1 = new ModelParameter(PopulateHelper.GetValue("alpha1", "a1", names, values, out found), a1Description);
this._s1 = new ModelParameter(PopulateHelper.GetValue("sigma1", "sigma", names, values, out found), s1Description);
this._a2 = new ModelParameter(PopulateHelper.GetValue("alpha2", "a2", names, values, out found), a2Description);
this._s2 = new ModelParameter(PopulateHelper.GetValue("sigma2", names, values, out found), s2Description);
this._rho = new ModelParameter(PopulateHelper.GetValue("rho", names, values, out found), rhoDescription);
}
/// <summary>
/// Populate editable fields from name and value vectors specific to VG.
/// </summary>
/// <param name="names">
/// An array with the names of the variables.
/// </param>
/// <param name="values">The values associated to the parameters in names.</param>
public void Populate(string[] names, double[] values)
{
bool found = false;
this.theta = new ModelParameter(PopulateHelper.GetValue("S0", names, values, out found), thetaDescription);
this.sigma = new ModelParameter(PopulateHelper.GetValue("theta", names, values, out found), sigmaDescription);
this.theta = new ModelParameter(PopulateHelper.GetValue("sigma", names, values, out found), thetaDescription);
this.theta = new ModelParameter(PopulateHelper.GetValue("nu", names, values, out found), thetaDescription);
this.theta = new ModelParameter(PopulateHelper.GetValue("rate", names, values, out found), thetaDescription);
this.theta = new ModelParameter(PopulateHelper.GetValue("dividend", names, values, out found), thetaDescription);
}
/// <summary>
/// Populate editable fields from name and value vectors
/// specific to the CIR process.
/// </summary>
/// <param name="container">
/// The stochastic process which is being referenced to.
/// </param>
/// <param name="estimate">
/// The estimation result which contains values and names of parameters.
/// </param>
public void Populate(IStochasticProcess container, EstimationResult estimate)
{
bool found;
this.parameterValues = new double[4];
for (int i = 0; i < parameterNames.Length; i++)
{
this.parameterValues[i] = PopulateHelper.GetValue(parameterNames[i],
estimate.Names, estimate.Values,
out found);
Console.WriteLine("ParameterValues[{0}] = {1}\t ParameterNames[{0}] = {2}",
i, this.parameterValues[i], parameterNames[i]);
}
SetParametersValue();
}
/// <summary>
/// Populate editable fields from name and value vectors
/// specific to the Heston extended process.
/// </summary>
/// <param name="stocProcess">
/// The stochastic process which is being referenced to.
/// </param>
/// <param name="estimate">
/// The estimation result which contains values and names of parameters.
/// It will be searched for S0, kappa, theta, sigma, V0, r, q and rho.
/// </param>
public void Populate(IStochasticProcess stocProcess, EstimationResult estimate)
{
bool found;
this.S0 = new ModelParameter(PopulateHelper.GetValue("S0", estimate.Names, estimate.Values, out found), this.S0.Description);
this.k = new ModelParameter(PopulateHelper.GetValue("kappa", estimate.Names, estimate.Values, out found), this.k.Description);
this.theta = new ModelParameter(PopulateHelper.GetValue("theta", estimate.Names, estimate.Values, out found), this.theta.Description);
this.sigma = new ModelParameter(PopulateHelper.GetValue("sigma", estimate.Names, estimate.Values, out found), this.sigma.Description);
this.V0 = new ModelParameter(PopulateHelper.GetValue("V0", estimate.Names, estimate.Values, out found), this.V0.Description);
this.r = new ModelParameter(PopulateHelper.GetValue("r", estimate.Names, estimate.Values, out found), this.r.Description);
this.q = new ModelParameter(PopulateHelper.GetValue("q", estimate.Names, estimate.Values, out found), this.q.Description);
int index = stocProcess.NoiseIndex;
ProjectProcess prj = stocProcess.Context as ProjectProcess;
// Updates the correlation.
prj.Processes.r.Set(index, index + 1, (RightValue)PopulateHelper.GetValue("rho", estimate.Names, estimate.Values, out found));
}
private void WhereClauseForm_Load(object sender, System.EventArgs e)
{
PopulateHelper helper = new PopulateHelper(data, null);
string[] columns = SqlSync.DbInformation.InfoHelper.GetColumnNames(this.tableName, this.data);
for (int i = 0; i < columns.Length; i++)
{
lstColumns.Items.Add(columns[i]);
}
//Pre-check exising "Update key selections"
for (int i = 0; i < columns.Length; i++)
{
lstUpdateKeyColumns.Items.Add(columns[i]);
for (int j = 0; j < this.checkKeyColumns.Length; j++)
{
if (columns[i].Trim().ToUpper() == this.checkKeyColumns[j].Trim().ToUpper())
{
lstUpdateKeyColumns.Items[lstUpdateKeyColumns.Items.Count - 1].Checked = true;
break;
}
}
}
}
public void TestCalibration()
{
InterestRateMarketData IData = InterestRateMarketData.FromFile("../../TestData/IRMD-sample.xml");
CallPriceMarketData HData = CallPriceMarketData.FromFile("../../TestData/CallData-sample.xml");
//InterestRateMarketData IData = InterestRateMarketData.FromFile("../../../EquityModels.Tests/TestData/IRMD-EU-30102012-close.xml");
//CallPriceMarketData HData = CallPriceMarketData.FromFile("../../../EquityModels.Tests/TestData/30102012-SX5E_Index-HestonData.xml");
//CallPriceMarketData HData = ObjectSerialization.ReadFromXMLFile("../../../EquityModels.Tests/TestData/FTSE.xml") as CallPriceMarketData;
List <object> l = new List <object>();
l.Add(IData.DiscountingCurve);
l.Add(HData);
DupireEstimator DE = new DupireEstimator();
DupireCalibrationSettings settings = new DupireCalibrationSettings();
settings.LocalVolatilityCalculation = LocalVolatilityCalculation.Method1;
//settings.LocalVolatilityCalculation = LocalVolatilityCalculation.QuantLib;
EstimationResult res = DE.Estimate(l, settings);
//int nmat = HData.Maturity.Length;
//int nstrike = HData.Strike.Length;
int i = 5; // Maturity.
int j = 4; // Strike.
Engine.MultiThread = true;
Document doc = new Document();
ProjectROV rov = new ProjectROV(doc);
doc.Part.Add(rov);
doc.DefaultProject.NMethods.m_UseAntiteticPaths = true;
int n_sim = 10000;
int n_steps = 500;
double strike = HData.Strike[j];
//double volatility = HData.Volatility[i, j];
/*
* PFunction2D.PFunction2D impvolfunc = new PFunction2D.PFunction2D(rov);
* impvolfunc = res.Objects[3] as PFunction2D.PFunction2D;
* impvolfunc.VarName = "impvol";
* rov.Symbols.Add(impvolfunc);
* double volatility = impvolfunc.Evaluate(HData.Maturity[i], HData.Strike[j]);
*/
double volatility = 0.2;
double maturity = HData.Maturity[i];
ModelParameter Pstrike = new ModelParameter(strike, string.Empty, "strike");
rov.Symbols.Add(Pstrike);
AFunction payoff = new AFunction(rov);
payoff.VarName = "payoff";
payoff.m_IndependentVariables = 1;
payoff.m_Value = (RightValue)("max(x1 - strike ; 0)");
rov.Symbols.Add(payoff);
bool found;
double S0 = PopulateHelper.GetValue("S0", res.Names, res.Values, out found);
ModelParameter PS0 = new ModelParameter(S0, string.Empty, "S0");
rov.Symbols.Add(PS0);
PFunction rfunc = new PFunction(rov);
rfunc = res.Objects[0] as PFunction;
rfunc.VarName = "r";
rov.Symbols.Add(rfunc);
PFunction qfunc = new PFunction(rov);
qfunc = res.Objects[1] as PFunction;
qfunc.VarName = "q";
rov.Symbols.Add(qfunc);
PFunction2D.PFunction2D volfunc = new PFunction2D.PFunction2D(rov);
volfunc = res.Objects[2] as PFunction2D.PFunction2D;
volfunc.VarName = "localvol";
rov.Symbols.Add(volfunc);
DupireProcess process = new DupireProcess();
process.s0 = (ModelParameter)"S0";
process.r = (ModelParameter)"@r";
process.q = (ModelParameter)"@q";
process.localVol = (ModelParameter)"@localvol";
double rate = rfunc.Evaluate(maturity);
double dy = qfunc.Evaluate(maturity);
StochasticProcessExtendible s = new StochasticProcessExtendible(rov, process);
rov.Processes.AddProcess(s);
// Set the discounting.
RiskFreeInfo rfi = rov.GetDiscountingModel() as RiskFreeInfo;
rfi.ActualizationType = EActualizationType.RiskFree;
rfi.m_deterministicRF = rate;
OptionTree op = new OptionTree(rov);
op.PayoffInfo.PayoffExpression = "payoff(v1)";
op.PayoffInfo.Timing.EndingTime.m_Value = (RightValue)maturity;
op.PayoffInfo.European = true;
rov.Map.Root = op;
rov.NMethods.Technology = ETechType.T_SIMULATION;
rov.NMethods.PathsNumber = n_sim;
rov.NMethods.SimulationSteps = n_steps;
ROVSolver solver = new ROVSolver();
solver.BindToProject(rov);
solver.DoValuation(-1);
if (rov.HasErrors)
{
rov.DisplayErrors();
}
Assert.IsFalse(rov.HasErrors);
ResultItem price = rov.m_ResultList[0] as ResultItem;
double samplePrice = price.value;
double sampleDevSt = price.stdDev / Math.Sqrt((double)n_sim);
Console.WriteLine("Surf = " + volfunc.Expr);
// Calculation of the theoretical value of the call.
double theoreticalPrice = BlackScholes.Call(rate, S0, strike, volatility, maturity, dy);
Console.WriteLine("Theoretical Price = " + theoreticalPrice.ToString());
Console.WriteLine("Monte Carlo Price = " + samplePrice);
Console.WriteLine("Standard Deviation = " + sampleDevSt.ToString());
double tol = 4.0 * sampleDevSt;
doc.WriteToXMLFile("Dupire.fair");
Assert.LessOrEqual(Math.Abs(theoreticalPrice - samplePrice), tol);
}
