added pricing engines for spread- and basket options

Python/test/test_basket_option.py

@@ -0,0 +1,174 @@
+"""
+ Copyright (C) 2024 Klaus Spanderen
+
+ This file is part of QuantLib, a free-software/open-source library
+ for financial quantitative analysts and developers - http://quantlib.org/
+
+ QuantLib is free software: you can redistribute it and/or modify it
+ under the terms of the QuantLib license.  You should have received a
+ copy of the license along with this program; if not, please email
+ <[email protected]>. The license is also available online at
+ <http://quantlib.org/license.shtml>.
+
+ This program is distributed in the hope that it will be useful, but WITHOUT
+ ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+ FOR A PARTICULAR PURPOSE.  See the license for more details.
+"""
+
+import unittest
+
+import QuantLib as ql
+
+
+class BasketOptionTest(unittest.TestCase):
+    def setUp(self):
+        self.todaysDate = ql.Date(26, ql.October, 2024)
+        ql.Settings.instance().evaluationDate = self.todaysDate
+
+    def tearDown(self):
+        ql.Settings.instance().evaluationDate = ql.Date()
+
+    def testThreeAssetSpreadOption(self):
+        """Testing three asset spread option"""
+
+        def build_process(s: float, q: float, v: float) -> ql.BlackScholesMertonProcess:
+            return ql.BlackScholesMertonProcess(
+                ql.QuoteHandle(ql.SimpleQuote(s)),
+                ql.YieldTermStructureHandle(
+                    ql.FlatForward(self.todaysDate, q, ql.Actual365Fixed())
+                ),
+                ql.YieldTermStructureHandle(
+                    ql.FlatForward(self.todaysDate, 0.05, ql.Actual365Fixed())
+                ),
+                ql.BlackVolTermStructureHandle(
+                    ql.BlackConstantVol(
+                        self.todaysDate, ql.TARGET(), v, ql.Actual365Fixed()
+                    )
+                ),
+            )
+
+        processes = [
+            build_process(100, 0.05, 0.3),
+            build_process(50, 0.07, 0.45),
+            build_process(50, 0.025, 0.2),
+        ]
+
+        processes_vector = ql.GeneralizedBlackScholesProcessVector(processes)
+
+        rho = ql.Matrix([[1.0, 0.2, -0.1], [0.2, 1.0, -0.3], [-0.1, -0.3, 1.0]])
+
+        exercise = ql.EuropeanExercise(self.todaysDate + ql.Period(1, ql.Years))
+        payoff = ql.PlainVanillaPayoff(ql.Option.Call, 2.0)
+
+        basket_option = ql.BasketOption(
+            ql.AverageBasketPayoff(payoff, ql.Array([1, -1, -1])), exercise
+        )
+
+        expected = 11.932739641
+
+        basket_option.setPricingEngine(ql.ChoiBasketEngine(processes_vector, rho, 10))
+        self.assertAlmostEqual(basket_option.NPV(), expected)
+
+        basket_option.setPricingEngine(ql.DengLiZhouBasketEngine(processes_vector, rho))
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+        basket_option.setPricingEngine(
+            ql.MCEuropeanBasketEngine(
+                ql.StochasticProcessArray(processes, rho),
+                "lowdiscrepancy",
+                timeSteps=1,
+                requiredTolerance=0.1,
+            )
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+        basket_option.setPricingEngine(
+            ql.FdndimBlackScholesVanillaEngine(
+                processes_vector, rho, ql.UnsignedIntVector([25, 15, 15]), 15
+            )
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+    def testTwoAssetSpreadOption(self):
+        """Testing two asset spread option"""
+
+        def build_process(s: float, v: float) -> ql.BlackProcess:
+            return ql.BlackProcess(
+                ql.QuoteHandle(ql.SimpleQuote(s)),
+                ql.YieldTermStructureHandle(
+                    ql.FlatForward(self.todaysDate, 0.05, ql.Actual365Fixed())
+                ),
+                ql.BlackVolTermStructureHandle(
+                    ql.BlackConstantVol(
+                        self.todaysDate, ql.TARGET(), v, ql.Actual365Fixed()
+                    )
+                ),
+            )
+
+        p1 = build_process(100, 0.3)
+        p2 = build_process(90, 0.45)
+        rho = -0.75
+        rho_m = ql.Matrix([[1, rho], [rho, 1]])
+
+        processes_vector = ql.GeneralizedBlackScholesProcessVector([p1, p2])
+
+        exercise = ql.EuropeanExercise(self.todaysDate + ql.Period(6, ql.Months))
+        payoff = ql.PlainVanillaPayoff(ql.Option.Put, 10.0)
+        basket_option = ql.BasketOption(ql.SpreadBasketPayoff(payoff), exercise)
+
+        expected = 17.96241322097977
+
+        basket_option.setPricingEngine(ql.ChoiBasketEngine(processes_vector, rho_m, 15))
+        self.assertAlmostEqual(basket_option.NPV(), expected, 10)
+
+        basket_option.setPricingEngine(
+            ql.DengLiZhouBasketEngine(processes_vector, rho_m)
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 4)
+
+        basket_option.setPricingEngine(ql.KirkEngine(p1, p2, rho))
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+        basket_option.setPricingEngine(ql.BjerksundStenslandSpreadEngine(p1, p2, rho))
+        self.assertAlmostEqual(basket_option.NPV(), expected, 2)
+
+        basket_option.setPricingEngine(
+            ql.OperatorSplittingSpreadEngine(
+                p1, p2, rho, ql.OperatorSplittingSpreadEngine.First
+            )
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+        basket_option.setPricingEngine(
+            ql.OperatorSplittingSpreadEngine(
+                p1, p2, rho, ql.OperatorSplittingSpreadEngine.Second
+            )
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 2)
+
+        basket_option.setPricingEngine(
+            ql.FdndimBlackScholesVanillaEngine(
+                processes_vector, rho_m, ql.UnsignedIntVector([25, 25]), 15
+            )
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+        basket_option.setPricingEngine(
+            ql.Fd2dBlackScholesVanillaEngine(p1, p2, rho, xGrid=25, yGrid=25, tGrid=15)
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+        basket_option.setPricingEngine(
+            ql.MCEuropeanBasketEngine(
+                ql.StochasticProcessArray([p1, p2], rho_m),
+                "lowdiscrepancy",
+                timeSteps=1,
+                requiredTolerance=0.1,
+            )
+        )
+        self.assertAlmostEqual(basket_option.NPV(), expected, 1)
+
+
+if __name__ == "__main__":
+    print("testing QuantLib", ql.__version__)
+    unittest.main(verbosity=2)

SWIG/basketoptions.i

@@ -1,10 +1,10 @@
-
 /*
  Copyright (C) 2000, 2001, 2002, 2003 RiskMap srl
  Copyright (C) 2003, 2004, 2005, 2006, 2007, 2008 StatPro Italia srl
  Copyright (C) 2005 Dominic Thuillier
  Copyright (C) 2007 Joseph Wang
  Copyright (C) 2018, 2019 Matthias Lungwitz
+ Copyright (C) 2024 Klaus Spanderen
 
  This file is part of QuantLib, a free-software/open-source library
  for financial quantitative analysts and developers - http://quantlib.org/
@@ -172,8 +172,8 @@ class MCAmericanBasketEngine : public PricingEngine {
                                BigInteger seed = 0,
                                Size nCalibrationSamples = Null<Size>(),
                                Size polynomOrder = 2,
-                               LsmBasisSystem::PolynomialType polynomType 
-                                  	= LsmBasisSystem::Monomial) {
+                               LsmBasisSystem::PolynomialType polynomType
+                                      = LsmBasisSystem::Monomial) {
             return new MCAmericanBasketEngine<RNG>(process,
                                                    timeSteps,
                                                    timeStepsPerYear,
@@ -233,6 +233,8 @@ class MCAmericanBasketEngine : public PricingEngine {
 %{
 using QuantLib::StulzEngine;
 using QuantLib::KirkEngine;
+using QuantLib::BjerksundStenslandSpreadEngine;
+using QuantLib::OperatorSplittingSpreadEngine;
 using QuantLib::Fd2dBlackScholesVanillaEngine;
 %}
 
@@ -252,17 +254,104 @@ class KirkEngine : public PricingEngine {
                Real correlation);
 };
 
+%shared_ptr(BjerksundStenslandSpreadEngine)
+class BjerksundStenslandSpreadEngine : public PricingEngine {
+  public:
+    BjerksundStenslandSpreadEngine(
+        const ext::shared_ptr<BlackProcess>& process1,
+        const ext::shared_ptr<BlackProcess>& process2,
+        Real correlation);
+};
+
+%shared_ptr(OperatorSplittingSpreadEngine)
+class OperatorSplittingSpreadEngine : public PricingEngine {
+  public:
+    enum Order {First, Second};
+    OperatorSplittingSpreadEngine(
+        const ext::shared_ptr<BlackProcess>& process1,
+        const ext::shared_ptr<BlackProcess>& process2,
+        Real correlation,
+        Order order = Second);
+};
+
 %shared_ptr(Fd2dBlackScholesVanillaEngine)
 class Fd2dBlackScholesVanillaEngine : public PricingEngine {
+    #if !defined(SWIGJAVA) && !defined(SWIGCSHARP)
+    %feature("kwargs") Fd2dBlackScholesVanillaEngine;
+    #endif
+  public:
+    Fd2dBlackScholesVanillaEngine(
+        const ext::shared_ptr<GeneralizedBlackScholesProcess>& p1,
+        const ext::shared_ptr<GeneralizedBlackScholesProcess>& p2,
+        Real correlation,
+        Size xGrid = 100, Size yGrid = 100,
+        Size tGrid = 50, Size dampingSteps = 0,
+        const FdmSchemeDesc& schemeDesc = FdmSchemeDesc::Hundsdorfer(),
+        bool localVol = false,
+        Real illegalLocalVolOverwrite = -Null<Real>());
+};
+
+%{
+using QuantLib::ChoiBasketEngine;
+using QuantLib::DengLiZhouBasketEngine;
+using QuantLib::FdndimBlackScholesVanillaEngine;
+%}
+
+#if defined(SWIGCSHARP)
+SWIG_STD_VECTOR_ENHANCED( ext::shared_ptr<GeneralizedBlackScholesProcess> )
+#endif
+%template(GeneralizedBlackScholesProcessVector)
+std::vector<ext::shared_ptr<GeneralizedBlackScholesProcess> >;
+
+
+%shared_ptr(ChoiBasketEngine)
+class ChoiBasketEngine : public PricingEngine {
+    #if !defined(SWIGJAVA) && !defined(SWIGCSHARP)
+    %feature("kwargs") ChoiBasketEngine;
+    #endif
   public:
-    Fd2dBlackScholesVanillaEngine(const ext::shared_ptr<GeneralizedBlackScholesProcess>& p1,
-                const ext::shared_ptr<GeneralizedBlackScholesProcess>& p2,
-                Real correlation,
-                Size xGrid = 100, Size yGrid = 100, 
-                Size tGrid = 50, Size dampingSteps = 0,
-                const FdmSchemeDesc& schemeDesc = FdmSchemeDesc::Hundsdorfer(),
-                bool localVol = false,
-                Real illegalLocalVolOverwrite = -Null<Real>());
+    ChoiBasketEngine(
+        std::vector<ext::shared_ptr<GeneralizedBlackScholesProcess> > processes,
+        Matrix rho,
+        Real lambda = 10.0,
+        Size maxNrIntegrationSteps = std::numeric_limits<Size>::max(),
+        bool calcfwdDelta = false,
+        bool controlVariate = false);
+};
+
+%shared_ptr(DengLiZhouBasketEngine)
+class DengLiZhouBasketEngine : public PricingEngine {
+    #if !defined(SWIGJAVA) && !defined(SWIGCSHARP)
+    %feature("kwargs") DengLiZhouBasketEngine;
+    #endif
+  public:
+    DengLiZhouBasketEngine(
+        std::vector<ext::shared_ptr<GeneralizedBlackScholesProcess> > processes,
+        Matrix rho);
+};
+
+%shared_ptr(FdndimBlackScholesVanillaEngine)
+class FdndimBlackScholesVanillaEngine : public PricingEngine {
+  public:
+      FdndimBlackScholesVanillaEngine(
+        std::vector<ext::shared_ptr<GeneralizedBlackScholesProcess> > processes,
+        Matrix rho, Size xGrid, Size tGrid = 50,
+        Size dampingSteps = 0,
+        const FdmSchemeDesc& schemeDesc = FdmSchemeDesc::Hundsdorfer());
+
+    %extend {
+        FdndimBlackScholesVanillaEngine(
+            std::vector<ext::shared_ptr<GeneralizedBlackScholesProcess> > processes,
+            Matrix rho,
+            const std::vector<unsigned int>& dim,
+            Size tGrid = 50,
+            Size dampingSteps = 0,
+            const FdmSchemeDesc& schemeDesc = FdmSchemeDesc::Hundsdorfer()) {
+                return new FdndimBlackScholesVanillaEngine(
+                    processes, rho, to_vector<Size>(dim), tGrid, dampingSteps, schemeDesc
+                );
+            }
+     }
 };
 
 %{

SWIG/fdm.i

@@ -617,6 +617,7 @@ using QuantLib::FdmDupire1dOp;
 using QuantLib::FdmBlackScholesFwdOp;
 using QuantLib::FdmHestonFwdOp;
 using QuantLib::FdmSquareRootFwdOp;
+using QuantLib::FdmWienerOp;
 
 typedef BoundaryCondition<FdmLinearOp> FdmBoundaryCondition;
 typedef std::vector<ext::shared_ptr<FdmBoundaryCondition> > FdmBoundaryConditionSet;
@@ -885,6 +886,15 @@ class FdmHestonFwdOp : public FdmLinearOpComposite {
             = ext::shared_ptr<LocalVolTermStructure>());
 };
 
+%shared_ptr(FdmWienerOp)
+class FdmWienerOp : public FdmLinearOpComposite {
+  public:
+    FdmWienerOp(
+        ext::shared_ptr<FdmMesher> mesher,
+        ext::shared_ptr<YieldTermStructure> rTS,
+        Array lambdas);
+};
+
 %{
 using QuantLib::TripleBandLinearOp;
 using QuantLib::FirstDerivativeOp;

SWIG/linearalgebra.i

@@ -604,13 +604,16 @@ class Matrix {
 using QuantLib::inverse;
 using QuantLib::pseudoSqrt;
 using QuantLib::SalvagingAlgorithm;
+using QuantLib::CholeskyDecomposition;
+using QuantLib::CholeskySolveFor;
+using QuantLib::SymmetricSchurDecomposition;
 %}
 
 struct SalvagingAlgorithm {
     #if defined(SWIGPYTHON)
     %rename(NoAlgorithm) None;
     #endif
-    enum Type { None, Spectral };
+    enum Type {None, Spectral, Hypersphere, LowerDiagonal, Higham, Principal};
 };
 
 Matrix inverse(const Matrix& m);
@@ -627,6 +630,16 @@ class SVD {
     const Array& singularValues() const;
 };
 
+Matrix CholeskyDecomposition(const Matrix& m, bool flexible = false);
+Array CholeskySolveFor(const Matrix& L, const Array& b);
+
+class SymmetricSchurDecomposition {
+  public:
+    SymmetricSchurDecomposition(const Matrix &s);
+    const Array& eigenvalues() const;
+    const Matrix& eigenvectors() const;
+};
+
 %{
 using QuantLib::BiCGstab;
 using QuantLib::GMRES;