/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of NVIDIA CORPORATION nor the names of its * contributors may be used to endorse or promote products derived * from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ #include /////////////////////////////////////////////////////////////////////////////// // Polynomial approximation of cumulative normal distribution function /////////////////////////////////////////////////////////////////////////////// static double CND(double d) { const double A1 = 0.31938153; const double A2 = -0.356563782; const double A3 = 1.781477937; const double A4 = -1.821255978; const double A5 = 1.330274429; const double RSQRT2PI = 0.39894228040143267793994605993438; double K = 1.0 / (1.0 + 0.2316419 * fabs(d)); double cnd = RSQRT2PI * exp(-0.5 * d * d) * (K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5))))); if (d > 0) cnd = 1.0 - cnd; return cnd; } /////////////////////////////////////////////////////////////////////////////// // Black-Scholes formula for both call and put /////////////////////////////////////////////////////////////////////////////// static void BlackScholesBodyCPU(float &callResult, float &putResult, float Sf, // Stock price float Xf, // Option strike float Tf, // Option years float Rf, // Riskless rate float Vf // Volatility rate ) { double S = Sf, X = Xf, T = Tf, R = Rf, V = Vf; double sqrtT = sqrt(T); double d1 = (log(S / X) + (R + 0.5 * V * V) * T) / (V * sqrtT); double d2 = d1 - V * sqrtT; double CNDD1 = CND(d1); double CNDD2 = CND(d2); // Calculate Call and Put simultaneously double expRT = exp(-R * T); callResult = (float)(S * CNDD1 - X * expRT * CNDD2); putResult = (float)(X * expRT * (1.0 - CNDD2) - S * (1.0 - CNDD1)); } //////////////////////////////////////////////////////////////////////////////// // Process an array of optN options //////////////////////////////////////////////////////////////////////////////// extern "C" void BlackScholesCPU(float *h_CallResult, float *h_PutResult, float *h_StockPrice, float *h_OptionStrike, float *h_OptionYears, float Riskfree, float Volatility, int optN) { for (int opt = 0; opt < optN; opt++) BlackScholesBodyCPU(h_CallResult[opt], h_PutResult[opt], h_StockPrice[opt], h_OptionStrike[opt], h_OptionYears[opt], Riskfree, Volatility); }