private static bool CalculateLinearMarginBalanceInternal(Portfolio portfolio, bool[] zeros, double[,] sigma, double[] profit, double[] margin, PortfolioInput input, Vector[] balance)
{
int count = 0;
Dictionary <int, int> map = new Dictionary <int, int>();
for (int index = 0; index < zeros.Length; ++index)
{
bool status = zeros[index];
if (!status)
{
map[map.Count] = index;
++count;
}
}
if (0 == count)
{
return(true); // nothing to do
}
// create sub-matrix
double[,] _sigma = new double[count, count];
double[] _profit = new double[count];
double[] _margin = new double[count];
for (int row = 0; row < count; ++row)
{
int r = map[row];
_profit[row] = profit[r];
_margin[row] = margin[r];
for (int column = 0; column < count; ++column)
{
int c = map[column];
_sigma[row, column] = sigma[r, c];
}
}
double[,] _balance = new double[balance.Length, count];
for (int row = 0; row < balance.Length; ++row)
{
int r = row;
for (int column = 0; column < count; ++column)
{
int c = map[column];
_balance[row, column] = balance[row][c];
}
}
// calculate factor and check it
double factor = NumericalMethods.Sqrt(_sigma.Maximum());
if (factor <= 0)
{
string st = string.Format("Runtime error: invalid factor = {0}", factor);
throw new InvalidOperationException(st);
}
// normalize data
NumericalMethods.Multiply(_sigma, 1 / factor / factor);
NumericalMethods.Multiply(_profit, 1 / factor);
// execute mathematica script
MathArgs args = new MathArgs();
args.Add("$profit", _profit);
args.Add("$reliability", input.Reliability);
args.Add("$covariance", _sigma);
args.Add("$loss", input.MaximumLoss / factor);
args.Add("$profit", _profit);
args.Add("$balance", _balance);
args.Add("$margin", _margin);
//args.Add("$margin", m);
double marginThreshold = (input.InitialDeposit - input.MaximumLoss) / input.MarginLevelThreshold;
args.Add("$marginThreshold", marginThreshold);
MathResult output = MathematicaKernel.Execute(s_portfolioMarginBalance, args);
double[] coefficients = (double[])output["result"];
double p = (double)output["profit"];
if (0 == p)
{
return(true);
}
// check results
bool result = FastPositiveMinimalThreshold(zeros, input.MinimumCoefficientValue, count, map, coefficients);
if (!result)
{
return(result);
}
// prepare results
for (int index = 0; index < count; ++index)
{
portfolio.Coefficients[map[index]] = coefficients[index];
}
portfolio.Profit = (double)output["profit"] * factor;
portfolio.When = (double)output["when"];
return(result);
}
