Esempio n. 1
0
        public static Portfolio CalculateLinear(double[,] equity, double reliability, double maximumLoss, double minimumCoefficientValue)
        {
            CalculateLinearValidation(reliability, maximumLoss);
            double[,] deltaEquity = NumericalMethods.CalculateAbsoluteVariation(equity);

            double[,] sigma = Statistics.CalculateCovarianceMatrix(deltaEquity);
            double factor = NumericalMethods.Sqrt(sigma.Maximum());

            if (factor <= 0)
            {
                string st = string.Format("Runtime error: invalid factor = {0}", factor);
                throw new InvalidOperationException(st);
            }
            NumericalMethods.Multiply(deltaEquity, 1 / factor);
            double[] profit = Statistics.CalculateAverage(deltaEquity);
            sigma = Statistics.CalculateCovarianceMatrix(deltaEquity);

            MathArgs args = new MathArgs();

            args.Add("$profit", profit);
            args.Add("$reliability", reliability);
            args.Add("$covariance", sigma);
            args.Add("$loss", maximumLoss / factor);
            args.Add("$coefficient", minimumCoefficientValue);
            Dictionary <string, object> output = MathematicaKernel.Execute(s_portfolioDiscrete, args);
            Portfolio result = new Portfolio();

            result.Profit       = (double)output["profit"] * factor;
            result.When         = (double)output["when"];
            result.Coefficients = (double[])output["result"];
            return(result);
        }
Esempio n. 2
0
        private static bool CalculateLinearFastInternal(Portfolio portfolio, bool[] zeros, double[,] sigma, double[] profit, double[] margin, double reliability, double maximumLoss,
                                                        double minimumCoefficientValue, double marginThreshold)
        {
            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 < _profit.Length; ++row)
            {
                int r = map[row];
                _profit[row] = profit[r];
                _margin[row] = margin[r];
                for (int column = 0; column < _profit.Length; ++column)
                {
                    int c = map[column];
                    _sigma[row, column] = sigma[r, 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);
            NumericalMethods.Multiply(_margin, 1 / factor);

            MathArgs args = new MathArgs();

            args.Add("$profit", _profit);
            args.Add("$reliability", reliability);
            args.Add("$covariance", _sigma);
            args.Add("$loss", maximumLoss / factor);
            args.Add("$threshold", marginThreshold / factor);
            args.Add("$margin", _margin);

            Dictionary <string, object> output = MathematicaKernel.Execute(s_portfolioMargin, args);

            double[] coefficients = (double[])output["result"];
            // check results
            bool result = FastPositiveMinimalThreshold(zeros, 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);
        }