| 1 | /* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */ |
| 2 | |
| 3 | /* |
| 4 | Copyright (C) 2001, 2002, 2003 Sadruddin Rejeb |
| 5 | Copyright (C) 2005 StatPro Italia srl |
| 6 | |
| 7 | This file is part of QuantLib, a free-software/open-source library |
| 8 | for financial quantitative analysts and developers - http://quantlib.org/ |
| 9 | |
| 10 | QuantLib is free software: you can redistribute it and/or modify it |
| 11 | under the terms of the QuantLib license. You should have received a |
| 12 | copy of the license along with this program; if not, please email |
| 13 | <quantlib-dev@lists.sf.net>. The license is also available online at |
| 14 | <http://quantlib.org/license.shtml>. |
| 15 | |
| 16 | This program is distributed in the hope that it will be useful, but WITHOUT |
| 17 | ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
| 18 | FOR A PARTICULAR PURPOSE. See the license for more details. |
| 19 | */ |
| 20 | |
| 21 | #include <ql/methods/lattices/trinomialtree.hpp> |
| 22 | #include <ql/stochasticprocess.hpp> |
| 23 | |
| 24 | namespace QuantLib { |
| 25 | |
| 26 | TrinomialTree::TrinomialTree( |
| 27 | const ext::shared_ptr<StochasticProcess1D>& process, |
| 28 | const TimeGrid& timeGrid, |
| 29 | bool isPositive) |
| 30 | : Tree<TrinomialTree>(timeGrid.size()), dx_(1, 0.0), timeGrid_(timeGrid) { |
| 31 | x0_ = process->x0(); |
| 32 | |
| 33 | Size nTimeSteps = timeGrid.size() - 1; |
| 34 | QL_REQUIRE(nTimeSteps > 0, "null time steps for trinomial tree" ); |
| 35 | |
| 36 | Integer jMin = 0; |
| 37 | Integer jMax = 0; |
| 38 | |
| 39 | for (Size i=0; i<nTimeSteps; i++) { |
| 40 | Time t = timeGrid[i]; |
| 41 | Time dt = timeGrid.dt(i); |
| 42 | |
| 43 | //Variance must be independent of x |
| 44 | Real v2 = process->variance(t0: t, x0: 0.0, dt); |
| 45 | Volatility v = std::sqrt(x: v2); |
| 46 | dx_.push_back(x: v*std::sqrt(x: 3.0)); |
| 47 | |
| 48 | Branching branching; |
| 49 | for (Integer j=jMin; j<=jMax; j++) { |
| 50 | Real x = x0_ + j*dx_[i]; |
| 51 | Real m = process->expectation(t0: t, x0: x, dt); |
| 52 | auto temp = Integer(std::floor(x: (m - x0_) / dx_[i + 1] + 0.5)); |
| 53 | |
| 54 | if (isPositive) { |
| 55 | while (x0_+(temp-1)*dx_[i+1]<=0) { |
| 56 | temp++; |
| 57 | } |
| 58 | } |
| 59 | |
| 60 | Real e = m - (x0_ + temp*dx_[i+1]); |
| 61 | Real e2 = e*e; |
| 62 | Real e3 = e*std::sqrt(x: 3.0); |
| 63 | |
| 64 | Real p1 = (1.0 + e2/v2 - e3/v)/6.0; |
| 65 | Real p2 = (2.0 - e2/v2)/3.0; |
| 66 | Real p3 = (1.0 + e2/v2 + e3/v)/6.0; |
| 67 | |
| 68 | branching.add(k: temp, p1, p2, p3); |
| 69 | } |
| 70 | branchings_.push_back(x: branching); |
| 71 | |
| 72 | jMin = branching.jMin(); |
| 73 | jMax = branching.jMax(); |
| 74 | } |
| 75 | } |
| 76 | |
| 77 | } |
| 78 | |
| 79 | |