Java tutorial
/** * Copyright (C) 2009 - present by OpenGamma Inc. and the OpenGamma group of companies * * Please see distribution for license. */ package com.opengamma.analytics.financial.model.option.pricing.analytic; import org.apache.commons.lang.Validate; import com.opengamma.analytics.financial.model.option.definition.StandardOptionDataBundle; import com.opengamma.analytics.financial.model.option.definition.SupershareOptionDefinition; import com.opengamma.analytics.math.function.Function1D; import com.opengamma.analytics.math.statistics.distribution.NormalDistribution; import com.opengamma.analytics.math.statistics.distribution.ProbabilityDistribution; /** * Class for pricing supershare options (see {@link com.opengamma.analytics.financial.model.option.definition.SupershareOptionDefinition}). * <p> * The price is calculated using the formula: * $$ * \begin{align*} * w = \frac{S e^{(b-r)T}}{K_L}(N(d_1) - N(d_2)) * \end{align*} * $$ * where * $$ * \begin{align*} * d_1 &= \frac{\ln{\frac{S}{K_L}} + (b + \frac{\sigma^2}{2})T}{\sigma\sqrt{T}}\\ * d_2 &= \frac{\ln{\frac{S}{K_H}} + (b + \frac{\sigma^2}{2})T}{\sigma\sqrt{T}} * \end{align*} * $$ * */ public class SupershareOptionModel extends AnalyticOptionModel<SupershareOptionDefinition, StandardOptionDataBundle> { private static final ProbabilityDistribution<Double> NORMAL = new NormalDistribution(0, 1); /** * {@inheritDoc} */ @Override public Function1D<StandardOptionDataBundle, Double> getPricingFunction( final SupershareOptionDefinition definition) { Validate.notNull(definition, "definition"); return new Function1D<StandardOptionDataBundle, Double>() { @SuppressWarnings("synthetic-access") @Override public Double evaluate(final StandardOptionDataBundle data) { Validate.notNull(data, "data"); final double s = data.getSpot(); final double t = definition.getTimeToExpiry(data.getDate()); final double r = data.getInterestRate(t); final double b = data.getCostOfCarry(); final double lower = definition.getLowerBound(); final double upper = definition.getUpperBound(); final double sigma = data.getVolatility(t, lower); final double d1 = getD1(s, lower, t, sigma, b); final double d2 = getD1(s, upper, t, sigma, b); return s * Math.exp(t * (b - r)) * (NORMAL.getCDF(d1) - NORMAL.getCDF(d2)) / lower; } }; } }