Inheritance: IEstimationSettings
示例#1
0
        public EstimationResult Estimate(System.Collections.Generic.List<object> marketData, IEstimationSettings settings = null, IController controller = null, System.Collections.Generic.Dictionary<string, object> properties = null)
        {
            CurveMarketData discountingCurve = (CurveMarketData)marketData[0];
            CallPriceMarketData Hdataset = (CallPriceMarketData)marketData[1];

            //gets the settings
            calibrationSettings = settings as DupireCalibrationSettings;

            //return this.FairmatEstimate(discountingCurve, Hdataset);
            // Removed quantlib estimate, it does not work correctly
            switch (calibrationSettings.LocalVolatilityCalculation)
            {
                case LocalVolatilityCalculation.Method1:
                    return this.FairmatEstimate(discountingCurve, Hdataset);
                case LocalVolatilityCalculation.QuantLib:
                    return QuantLibEstimate(discountingCurve, Hdataset);
                default:
                    throw new NotImplementedException("Method not implemented");
            }
        }
示例#2
0
        public EstimationResult Estimate(System.Collections.Generic.List <object> marketData, IEstimationSettings settings = null, IController controller = null, System.Collections.Generic.Dictionary <string, object> properties = null)
        {
            CurveMarketData     discountingCurve = (CurveMarketData)marketData[0];
            CallPriceMarketData Hdataset         = (CallPriceMarketData)marketData[1];

            //gets the settings
            calibrationSettings = settings as DupireCalibrationSettings;


            //return this.FairmatEstimate(discountingCurve, Hdataset);
            // Removed quantlib estimate, it does not work correctly
            switch (calibrationSettings.LocalVolatilityCalculation)
            {
            case LocalVolatilityCalculation.Method1:
                return(this.FairmatEstimate(discountingCurve, Hdataset));

            case LocalVolatilityCalculation.QuantLib:
                return(QuantLibEstimate(discountingCurve, Hdataset));

            default:
                throw new NotImplementedException("Method not implemented");
            }
        }
        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);
        }