text: /* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
  
  /*
   Copyright (C) 2009 Sun Xiuxin
  
   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
   <quantlib-dev@lists.sf.net>. 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.
  */
  
  #include <ql/models/marketmodels/evolvers/lognormalfwdrateiballand.hpp>
  #include <ql/models/marketmodels/marketmodel.hpp>
  #include <ql/models/marketmodels/evolutiondescription.hpp>
  #include <ql/models/marketmodels/browniangenerator.hpp>
  #include <ql/models/marketmodels/driftcomputation/lmmdriftcalculator.hpp>
  
  namespace QuantLib {
  
      LogNormalFwdRateiBalland::LogNormalFwdRateiBalland(
                             const boost::shared_ptr<MarketModel>& marketModel,
                             const BrownianGeneratorFactory& factory,
                             const std::vector<Size>& numeraires,
                             Size initialStep)
      : marketModel_(marketModel),
        numeraires_(numeraires),
        initialStep_(initialStep),
        numberOfRates_(marketModel->numberOfRates()),
        numberOfFactors_(marketModel->numberOfFactors()),
        curveState_(marketModel->evolution().rateTimes()),
        forwards_(marketModel->initialRates()),
        displacements_(marketModel->displacements()),
        logForwards_(numberOfRates_), initialLogForwards_(numberOfRates_),
        initialDrifts_(numberOfRates_), brownians_(numberOfFactors_),
        correlatedBrownians_(numberOfRates_),
        rateTaus_(marketModel->evolution().rateTaus()),
        alive_(marketModel->evolution().firstAliveRate())
      {
          checkCompatibility(marketModel->evolution(), numeraires);
          QL_REQUIRE( isInTerminalMeasure(marketModel->evolution(), numeraires),
                      "terminal measure required for iBalland " );
  
          Size steps = marketModel->evolution().numberOfSteps();
  
          generator_ = factory.create(numberOfFactors_, steps-initialStep_);
  
          currentStep_ = initialStep_;
  
          calculators_.reserve(steps);
          fixedDrifts_.reserve(steps);
          for (Size j=0; j<steps; ++j) {
              const Matrix& A = marketModel->pseudoRoot(j);
              calculators_.push_back(LMMDriftCalculator(A,
                                                     displacements_,
                                                     marketModel->evolution().rateTaus(),
                                                     numeraires[j],
                                                     alive_[j]));
              const Matrix& C = marketModel->covariance(j);
              std::vector<Real> fixed(numberOfRates_);
              for (Size k=0; k<numberOfRates_; ++k) {
                  Real variance = C[k][k];
                  fixed[k] = -0.5*variance;
              }
              fixedDrifts_.push_back(fixed);
          }
  
          setForwards(marketModel_->initialRates());
      }
  
      const std::vector<Size>& LogNormalFwdRateiBalland::numeraires() const {
          return numeraires_;
      }
  
      void LogNormalFwdRateiBalland::setForwards(const std::vector<Real>& forwards)
      {
          QL_REQUIRE(forwards.size()==numberOfRates_,
                     "mismatch between forwards and rateTimes");
          for (Size i=0; i<numberOfRates_; ++i)
              initialLogForwards_[i] = std::log(forwards[i] +
                                                displacements_[i]);
          calculators_[initialStep_].compute(forwards, initialDrifts_);
      }
  
      void LogNormalFwdRateiBalland::setInitialState(const CurveState& cs) {
          setForwards(cs.forwardRates());
      }
  
      Real LogNormalFwdRateiBalland::startNewPath() {
          currentStep_ = initialStep_;
          std::copy(initialLogForwards_.begin(), initialLogForwards_.end(),
                    logForwards_.begin());
          return generator_->nextPath();
      }
  
      Real LogNormalFwdRateiBalland::advanceStep()
      {
          Real weight = generator_->nextStep(brownians_);
          const Matrix& A = marketModel_->pseudoRoot(currentStep_);
          const Matrix& C = marketModel_->covariance(currentStep_);
          const std::vector<Real>& fixedDrift = fixedDrifts_[currentStep_];
  
          Integer alive = alive_[currentStep_];
          Integer i;
          Real blFwd;
          std::vector<Real> g_(numberOfRates_);
  
          i = numberOfRates_-1;
          if ( i >= alive )
          {
              logForwards_[i] += fixedDrift[i];
              logForwards_[i] += std::inner_product( A.row_begin(i), A.row_end(i),
                                                     brownians_.begin(), 0.0 );
              forwards_[i] = std::exp(logForwards_[i]) - displacements_[i];
              blFwd = std::sqrt( marketModel_->initialRates()[i]*forwards_[i] );
              g_[i] = rateTaus_[i]*( blFwd+displacements_[i] )/
                      ( 1.0+rateTaus_[i]*blFwd );
          }
  
          Real drifts2;
          for ( i = numberOfRates_-2; i >= alive ; --i )
          {
              drifts2 = 0.0;
              for ( Size j = i+1; j < numberOfRates_ ; ++j )
                  drifts2 -= g_[j]*C[i][j];
              logForwards_[i] += drifts2 + fixedDrift[i];
              logForwards_[i] += std::inner_product( A.row_begin(i), A.row_end(i),
                                                     brownians_.begin(), 0.0);
              forwards_[i] = std::exp(logForwards_[i]) - displacements_[i];
  
              blFwd = std::sqrt( marketModel_->initialRates()[i]*forwards_[i] );
              g_[i] = rateTaus_[i]*( blFwd+displacements_[i] )/
                      ( 1.0+rateTaus_[i]*blFwd );
          }
  
          // update curve state
          curveState_.setOnForwardRates(forwards_);
  
          ++currentStep_;
  
          return weight;
      }
  
      Size LogNormalFwdRateiBalland::currentStep() const {
          return currentStep_;
      }
  
      const CurveState& LogNormalFwdRateiBalland::currentState() const {
          return curveState_;
      }
  
  }
  