/*
The example
python portfolio.py portfolio
reads in data and solves the portfolio models.
*/
public static void Main(string[] argv)
{
string name = argv[0];
MarkowitzData d = new MarkowitzData(name);
{
Console.WriteLine("\n-------------------------------------------------------------------");
Console.WriteLine("Basic Markowitz portfolio optimization");
Console.WriteLine("---------------------------------------------------------------------\n");
for(int i = 0; i < d.gammas.Length; ++i)
{
double res = BasicMarkowitz(d.n, d.mu, d.GT, d.x0, d.w, d.gammas[i]);
Console.WriteLine("Expected return: {0,-12:f4} Std. deviation: {1,-12:f4} ", res,d.gammas[i]);
}
}
{
// Some predefined alphas are chosen
double[] alphas = { 0.0, 0.01, 0.1, 0.25, 0.30, 0.35, 0.4, 0.45, 0.5, 0.75, 1.0, 1.5, 2.0, 3.0, 10.0 };
int niter = alphas.Length;
double[] frontier_mux = new double[niter];
double[] frontier_s = new double[niter];
EfficientFrontier(d.n,d.mu,d.GT,d.x0,d.w,alphas, frontier_mux, frontier_s);
Console.WriteLine("\n-------------------------------------------------------------------------");
Console.WriteLine("Efficient frontier\n") ;
Console.WriteLine("------------------------------------------------------------------------\n");
Console.WriteLine("{0,-12} {1,-12} {2,-12}", "alpha","return","risk") ;
for (int i = 0; i < frontier_mux.Length; ++i)
Console.WriteLine("{0,-12:f4} {0,-12:e4} {0,-12:e4}\n", alphas[i],frontier_mux[i],frontier_s[i]);
}
{
// Somewhat arbirtrary choice of m
double[] m = new double[d.n]; for (int i = 0; i < d.n; ++i) m[i] = 1.0e-2;
double[] x = new double[d.n];
double[] t = new double[d.n];
MarkowitzWithMarketImpact(d.n,d.mu,d.GT,d.x0,d.w,d.gammas[0],m, x,t);
Console.WriteLine("\n-----------------------------------------------------------------------");
Console.WriteLine("Markowitz portfolio optimization with market impact cost\n");
Console.WriteLine("------------------------------------------------------------------------\n");
Console.WriteLine("Expected return: {0:e4} Std. deviation: {1:e4} Market impact cost: {2:e4}\n",
dot(d.mu,x),
d.gammas[0],
dot(m,t));
}
{
double[] f = new double[d.n]; for (var i = 0; i < d.n; ++i) f[i] = 0.01;
double[] g = new double[d.n]; for (var i = 0; i < d.n; ++i) g[i] = 0.001;
MarkowitzWithTransactionsCost(d.n,d.mu,d.GT,d.x0,d.w,d.gammas[0],f,g);
}
}
/*
* The example
*
* python portfolio.py portfolio
*
* reads in data and solves the portfolio models.
*/
public static void Main(string[] argv)
{
string name = argv[0];
MarkowitzData d = new MarkowitzData(name);
{
Console.WriteLine("\n-------------------------------------------------------------------");
Console.WriteLine("Basic Markowitz portfolio optimization");
Console.WriteLine("---------------------------------------------------------------------\n");
for (int i = 0; i < d.gammas.Length; ++i)
{
double res = BasicMarkowitz(d.n, d.mu, d.GT, d.x0, d.w, d.gammas[i]);
Console.WriteLine("Expected return: {0,-12:f4} Std. deviation: {1,-12:f4} ", res, d.gammas[i]);
}
}
{
// Some predefined alphas are chosen
double[] alphas = { 0.0, 0.01, 0.1, 0.25, 0.30, 0.35, 0.4, 0.45, 0.5, 0.75, 1.0, 1.5, 2.0, 3.0, 10.0 };
int niter = alphas.Length;
double[] frontier_mux = new double[niter];
double[] frontier_s = new double[niter];
EfficientFrontier(d.n, d.mu, d.GT, d.x0, d.w, alphas, frontier_mux, frontier_s);
Console.WriteLine("\n-------------------------------------------------------------------------");
Console.WriteLine("Efficient frontier\n");
Console.WriteLine("------------------------------------------------------------------------\n");
Console.WriteLine("{0,-12} {1,-12} {2,-12}", "alpha", "return", "risk");
for (int i = 0; i < frontier_mux.Length; ++i)
{
Console.WriteLine("{0,-12:f4} {0,-12:e4} {0,-12:e4}\n", alphas[i], frontier_mux[i], frontier_s[i]);
}
}
{
// Somewhat arbirtrary choice of m
double[] m = new double[d.n]; for (int i = 0; i < d.n; ++i)
{
m[i] = 1.0e-2;
}
double[] x = new double[d.n];
double[] t = new double[d.n];
MarkowitzWithMarketImpact(d.n, d.mu, d.GT, d.x0, d.w, d.gammas[0], m, x, t);
Console.WriteLine("\n-----------------------------------------------------------------------");
Console.WriteLine("Markowitz portfolio optimization with market impact cost\n");
Console.WriteLine("------------------------------------------------------------------------\n");
Console.WriteLine("Expected return: {0:e4} Std. deviation: {1:e4} Market impact cost: {2:e4}\n",
dot(d.mu, x),
d.gammas[0],
dot(m, t));
}
{
double[] f = new double[d.n]; for (var i = 0; i < d.n; ++i)
{
f[i] = 0.01;
}
double[] g = new double[d.n]; for (var i = 0; i < d.n; ++i)
{
g[i] = 0.001;
}
MarkowitzWithTransactionsCost(d.n, d.mu, d.GT, d.x0, d.w, d.gammas[0], f, g);
}
}
