#!/usr/bin/python ############################################################################################## # Copyright (c) 2015, Michael Nowotny # All rights reserved. # # Redistribution and use in source and binary forms, with or without modification, # are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # 2. 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. # # 3. Neither the name of the copyright holder 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 AND CONTRIBUTORS # "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. ############################################################################################### import arrayfire as af import math import time def simulateHestonModel( T, N, R, mu, kappa, vBar, sigmaV, rho, x0, v0 ) : deltaT = T / (float)(N - 1) x = [af.constant(x0, R, dtype=af.Dtype.f32), af.constant(0, R, dtype=af.Dtype.f32)] v = [af.constant(v0, R, dtype=af.Dtype.f32), af.constant(0, R, dtype=af.Dtype.f32)] sqrtDeltaT = math.sqrt(deltaT) sqrtOneMinusRhoSquare = math.sqrt(1-rho**2) m = af.constant(0, 2, dtype=af.Dtype.f32) m[0] = rho m[1] = sqrtOneMinusRhoSquare zeroArray = af.constant(0, R, 1, dtype=af.Dtype.f32) for t in range(1, N) : tPrevious = (t + 1) % 2 tCurrent = t % 2 dBt = af.randn(R, 2, dtype=af.Dtype.f32) * sqrtDeltaT vLag = af.maxof(v[tPrevious], zeroArray) sqrtVLag = af.sqrt(vLag) x[tCurrent] = x[tPrevious] + (mu - 0.5 * vLag) * deltaT + sqrtVLag * dBt[:, 0] v[tCurrent] = vLag + kappa * (vBar - vLag) * deltaT + sigmaV * (sqrtVLag * af.matmul(dBt, m)) return (x[tCurrent], af.maxof(v[tCurrent], zeroArray)) def main(): T = 1 nT = 20 * T R_first = 1000 R = 5000000 x0 = 0 # initial log stock price v0 = 0.087**2 # initial volatility r = math.log(1.0319) # risk-free rate rho = -0.82 # instantaneous correlation between Brownian motions sigmaV = 0.14 # variance of volatility kappa = 3.46 # mean reversion speed vBar = 0.008 # mean variance k = math.log(0.95) # strike price # first run ( x, v ) = simulateHestonModel( T, nT, R_first, r, kappa, vBar, sigmaV, rho, x0, v0 ) # Price plain vanilla call option tic = time.time() ( x, v ) = simulateHestonModel( T, nT, R, r, kappa, vBar, sigmaV, rho, x0, v0 ) af.sync() toc = time.time() - tic K = math.exp(k) zeroConstant = af.constant(0, R, dtype=af.Dtype.f32) C_CPU = math.exp(-r * T) * af.mean(af.maxof(af.exp(x) - K, zeroConstant)) print("Time elapsed = {} secs".format(toc)) print("Call price = {}".format(C_CPU)) print(af.mean(v)) if __name__ == "__main__": main()