americanbasketprice.java

金融资产定价,随机过程,MONTE CARLO 模拟 JAVA 程序和文档资料

/*
 * AmericanBasketPrice.java
 *
 * Created on November 13, 2002, 8:47 PM
 */

package Examples.Pricing;

import Market.*;
import Options.*;
import Triggers.*;
import LinAlg.*;


/** Computes the price of the American option from the Haugh/Kogan paper 
 *  under the naive exercise policy for various values of the parameter alpha.
 *
 * @author  Michael J. Meyer
 */
public class AmericanBasketPrice {
    
    public static void main(String[] args)
    {
        
        long before, after;
        double time;
        
        // European price, one time step to horizon
        final int dim=5, 
                  T=10,
                  nPath=10000,
                  nBranch=1000;
        
        final double dt=3.0/T, r=0.05, q=0.1, sigma=0.2, K=100.0;
        
        

        // basket of uncorrelated assets, one time step to horizon
        final double[] S_0=new double[dim];
        for(int i=0;i<dim;i++)S_0[i]=100;
        DiagonalBasket 
        assets=new DiagonalBasket(1,3.0,S_0,r,q,sigma);
        

        // European call on maximum
        BasketOption 
        EuroCallOnMaximum=new BasketOption(assets,"eurocall"){
            
            public double currentDiscountedPayoff(){
                
                ColtVector[] S=get_underlying().get_S();
                double[] B=get_underlying().get_B();
                double max=0, S_iT;
                for(int i=0;i<dim;i++){ S_iT=S[1].getQuick(i);
                                        if(S_iT>max)max=S_iT; }
                return (max>K/B[1])? max-K/B[1] : 0;
            }
        }; // end CallOnMaximum
        

        double 
        euroPrice=EuroCallOnMaximum.discountedMonteCarloPrice(400000);
        
        System.out.println("euroPrice="+euroPrice);
        
        
       
         // American call on maximum
        assets=new DiagonalBasket(T,dt,S_0,r,q,sigma);
        
        
        AmericanBasketOption 
        CallOnMaximum=new AmericanBasketOption(assets){
            
            public double currentDiscountedPayoff(int t){
                
                ColtVector[] S=get_underlying().get_S();
                double[] B=get_underlying().get_B();
                double max=0, S_it;
                for(int i=0;i<dim;i++){ S_it=S[t].getQuick(i);
                                        if(S_it>max)max=S_it; }
                return (max>K/B[t])? max-K/B[t] : 0;
            }
        }; // end CallOnMaximum
        
        
        /* pure exercise policy and corresponding price
        before=System.currentTimeMillis();
        
        Trigger pureExercise=CallOnMaximum.pureExercise(nBranch);
        double  purePrice=
        CallOnMaximum.discountedMonteCarloPrice(nPath,pureExercise);
        
        after=System.currentTimeMillis();
        time=0.001*(after-before);
        
        System.out.println("purePrice="+purePrice+", time: "+time);
        */

                
        // cvx exercise policy and corresponding price
        before=System.currentTimeMillis();

        double alpha=0.85, beta=150;
        Trigger cvx=CallOnMaximum.convexTrigger(alpha,beta,nBranch);
        double  cvxPrice=
        CallOnMaximum.discountedMonteCarloPrice(nPath,cvx);
        
        after=System.currentTimeMillis();
        time=0.001*(after-before);
        
        System.out.println("cvxPrice="+cvxPrice+", time: "+time);
        
        /*
        // upper bound
        before=System.currentTimeMillis();
        double upperBd=CallOnMaximum.upperBound(nPath,naiveExercise);
        after=System.currentTimeMillis();
        time=0.001*(after-before);
        
        System.out.println("Upper bound = "+upperBd+", time: "+time);
        */

        
    } // end main
    
}