/*
 * (c) Copyright Christian P. Fries, Germany. All rights reserved. Contact: email@christian-fries.de.
 *
 * Created on 23.11.2011
 */
package net.finmath.montecarlo.assetderivativevaluation.products;

import net.finmath.exception.CalculationException;
import net.finmath.montecarlo.assetderivativevaluation.AssetModelMonteCarloSimulationInterface;
import net.finmath.stochastic.RandomVariableInterface;
import net.finmath.time.TimeDiscretizationInterface;

/**
 * Implements the valuation of an Asian option.
 * 
 * Given a model for an asset S, the Asian option with strike K, maturity T
 * and averaging points Ti for i = 1,...,n pays
 * 
* max(A(T) - K , 0) in T *
* where *
* A(T) = 1/n (S(T1)+ ... + S(Tn)) *
* * @author Christian Fries * @version 1.2 */ public class AsianOption extends AbstractAssetMonteCarloProduct { private final double maturity; private final double strike; private final TimeDiscretizationInterface timesForAveraging; /** * Construct a product representing an Asian option on an asset S (where S the asset with index 0 from the model - single asset case). * A(T) = 1/n sum_{i=1,...,n} S(t_i), where t_i are given observation times. * * @param strike The strike K in the option payoff max(A(T)-K,0). * @param maturity The maturity T in the option payoff maxAS(T)-K,0) * @param timesForAveraging The times t_i used in the calculation of A(T) = 1/n sum_{i=1,...,n} S(t_i). */ public AsianOption(double maturity, double strike, TimeDiscretizationInterface timesForAveraging) { super(); this.maturity = maturity; this.strike = strike; this.timesForAveraging = timesForAveraging; } /** * This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime. * Note: For a lattice this is often the value conditional to evalutationTime, for a Monte-Carlo simulation this is the (sum of) value discounted to evaluation time. * Cashflows prior evaluationTime are not considered. * * @param evaluationTime The time on which this products value should be observed. * @param model The model used to price the product. * @return The random variable representing the value of the product discounted to evaluation time * @throws net.finmath.exception.CalculationException Thrown if the valuation fails, specific cause may be available via the cause() method. */ @Override public RandomVariableInterface getValue(double evaluationTime, AssetModelMonteCarloSimulationInterface model) throws CalculationException { // Calculate average RandomVariableInterface average = model.getRandomVariableForConstant(0.0); for(double time : timesForAveraging) { RandomVariableInterface underlying = model.getAssetValue(time,0); average = average.add(underlying); } average = average.div(timesForAveraging.getNumberOfTimes()); // The payoff: values = max(underlying - strike, 0) RandomVariableInterface values = average.sub(strike).floor(0.0); // Discounting... RandomVariableInterface numeraireAtMaturity = model.getNumeraire(maturity); RandomVariableInterface monteCarloWeights = model.getMonteCarloWeights(maturity); values = values.div(numeraireAtMaturity).mult(monteCarloWeights); // ...to evaluation time. RandomVariableInterface numeraireAtEvalTime = model.getNumeraire(evaluationTime); RandomVariableInterface monteCarloProbabilitiesAtEvalTime = model.getMonteCarloWeights(evaluationTime); values = values.mult(numeraireAtEvalTime).div(monteCarloProbabilitiesAtEvalTime); return values; } }

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