

/*
 Copyright (C) 2000, 2001, 2002, 2003 RiskMap srl

 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 ferdinando@ametrano.net
 The license is also available online at http://quantlib.org/html/license.html

 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.
*/
/*! \file riskmeasures.hpp
    \brief Risk functions

    \fullpath
    ql/Math/%riskmeasures.hpp
*/

// $Id: riskmeasures.hpp,v 1.7.10.1 2002/12/31 18:40:37 nando Exp $

#ifndef quantlib_risk_measures_h
#define quantlib_risk_measures_h

#include <ql/null.hpp>
#include <ql/Math/normaldistribution.hpp>
#include <vector>


namespace QuantLib {

    namespace Math {

        //! Interface for risk functions
        class RiskMeasures {
          public:
            RiskMeasures() {}
            double potentialUpside(double percentile,
                                   double mean,
                                   double std) const ;
            double valueAtRisk(double percentile,
                               double mean,
                               double std) const ;
            double expectedShortfall(double percentile,
                                     double mean,
                                     double std) const ;
            double shortfall(double target,
                             double mean,
                             double std) const ;
            double averageShortfall(double target,
                                    double mean,
                                    double std) const ;
       };

        // inline definitions
        /*! \pre percentile must be in range 90%-100% */
        inline double RiskMeasures::potentialUpside(double percentile,
                                                     double mean,
                                                     double std) const {
            QL_REQUIRE(percentile<1.0 && percentile>=0.9,
                "RiskMeasures::potentialUpside : percentile (" +
                DoubleFormatter::toString(percentile) +
                ") out of range 90%-100%");

            Math::InvCumulativeNormalDistribution gInverse(mean, std);
            // PotenzialUpSide must be a gain
            // this means that it has to be MAX(dist(percentile), 0.0)
            return QL_MAX(gInverse(percentile), 0.0);
        }

        /*! \pre percentile must be in range 90%-100% */
        inline double RiskMeasures::valueAtRisk(double percentile,
                                           double mean,
                                           double std) const {
            QL_REQUIRE(percentile<1.0 && percentile>=0.9,
                "RiskMeasures::valueAtRisk : percentile (" +
                DoubleFormatter::toString(percentile) +
                ") out of range 90%-100%");

            Math::InvCumulativeNormalDistribution gInverse(mean, std);
            // VAR must be a loss
            // this means that it has to be MIN(dist(1.0-percentile), 0.0)
            // VAR must also be a positive quantity, so -MIN(*)
            return -QL_MIN(gInverse(1.0-percentile), 0.0);
        }

        /*! \pre percentile must be in range 90%-100% */
        inline double RiskMeasures::expectedShortfall(double percentile,
                                                 double mean,
                                                 double std) const {
            QL_REQUIRE(percentile<1.0 && percentile>=0.9,
                "RiskMeasures::expectedShortfall : percentile (" +
                DoubleFormatter::toString(percentile) +
                ") out of range 90%-100%");

            Math::InvCumulativeNormalDistribution gInverse(mean, std);
            double var = gInverse(1.0-percentile);
            Math::NormalDistribution g(mean, std);
            double result = mean - std*std*g(var)/(1.0-percentile);
            // expectedShortfall must be a loss
            // this means that it has to be MIN(result, 0.0)
            // expectedShortfall must also be a positive quantity, so -MIN(*)
            return -QL_MIN(result, 0.0);
        }

        inline double RiskMeasures::shortfall(double target,
                                         double mean,
                                         double std) const {
            Math::CumulativeNormalDistribution gIntegral(mean, std);
            return gIntegral(target);
        }

        inline double RiskMeasures::averageShortfall(double target,
                                                double mean,
                                                double std) const {
            Math::CumulativeNormalDistribution gIntegral(mean, std);
            Math::NormalDistribution g(mean, std);
            return ( (target-mean)*gIntegral(target) + std*std*g(target) );
        }

    }

}


#endif
