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quantjudge.com Evaluation report: Black Scholes challenge

John Lewis
Candidate Session
ID : 148
Mail : candidatemail1@email.com
Phone : 07391586609
Degree :
School/University : UCL
Experience : 6
Your comment :
Candidate comment: Candidat can leave a comment , which will be sent to your recruiter..
ID session : 4q9t
Started : 2018-07-08 00:57:02
Finished : 2018-07-08 01:00:51

Test Test type Absolute score Relative score
1. [C++] Black Scholes simulation Coding 5 / 5
85%
  Global score

5 / 5
.
1. [C++] Black Scholes simulation
1-1. Subject coding

Black Scholes simulation [C++]

1- Description:
This test consists of creating a European option pricer, under the Black-Scholes model (extended for dividends by Merton) based on simulation (monte carlo). A skeleton of this pricer is provided.


2- Objective:
The objective of this test is to Implement the following function BSSimul (...) to return the price of the option using the simulation method (a function BS (...) giving the price by the closed formula is provided to serve as your benchmark).


3- The skeleton code provided:
NormalFunctions.h // Math / utility function
BlackScholesSimulation.h // the file BSSimul based pricing (supplied with a Gaussian generator box-muller)


4- Note:
1- the only work to do is to complete the implementation of the BSSimul function (...) File BlackScholesSimulation.h

2-Your code does not print the screen unless you want to test / debuger in this case make sure you remove these impressions screen before submitting your solution

3- The run button allows you to run a unit test on your solution


Language : cpp    Compilation:Successfully   Marks Scored: 5/5
1-2. Unit test cases

Test name Candidate Output Value Correct output Execution time Memory consumption Result
Unit test14.244 4.230660.02 sec0 KB Passed
Unit test29.54605 9.585810.00 sec0 KB Passed
Unit test37.15622 7.131360.00 sec0 KB Passed
Unit test439.5632 39.5080.00 sec0 KB Passed
Unit test541.2614 41.33490.00 sec0 KB Passed

1-3. Candidate Source code

Main File: BlackScholesSimulation.h

// Black-Scholes by simulation.
// TestCandidat.com


#include <iostream>
#include <iomanip>
#include <vector>
#include <math.h>
#include <stdlib.h>
#include <time.h>
#include <algorithm>
#include "NormalFunctions.h"
using namespace std;

//BSSimul compute the price of an european option using simulation
    // S Spot Price
    // K Strike Price
    // T Maturity in Years
    // rf Interest Rate
    // q Dividend  yeild
    // v Volatility
    // PutCall 'P' for put and 'C' for call
    // Nsims Number of simulations

double BSSimul(double S,double K,double v,double T,double rf,double q,char PutCall) {

double u1,u2,Z;
double pi = 3.141592653589793;
int Nsims = 1e5; // Number of simulations
vector<double> ST(Nsims, 0.0);// Initialize terminal prices S(T)
vector<double> ST_K(Nsims, 0.0);// Initialize call payoff
vector<double> K_ST(Nsims, 0.0);// Initialize put payoff
for (int i=0; i<=Nsims-1; i++) {
// Independent uniform random variables
u1 = ((double)rand() / ((double)(RAND_MAX)+(double)(1)) );
u2 = ((double)rand() / ((double)(RAND_MAX)+(double)(1)) );
// Floor u1 to avoid errors with log function
u1 = max(u1,1.0e-10);
// Z ~ N(0,1) by Box-Muller transofmration
Z = sqrt(-2.0*log(u1)) * sin(2*pi*u2);
ST[i] = S*exp((rf - q - 0.5*v*v)*T + v*sqrt(T)*Z);// Simulated terminal price S(T)
ST_K[i] = max(ST[i] - K, 0.0);// Call payoff
K_ST[i] = max(K - ST[i], 0.0);// Put payoff
}
// Simulated prices as discounted average of terminal prices
double BSCallSim = exp(-rf*T)*VecMean(ST_K);
double BSPutSim  = exp(-rf*T)*VecMean(K_ST);
if(PutCall =='C')
    return BSCallSim;
else
    return BSPutSim;
}