Esempio n. 1
0
        public static Portfolio CalculateLinearFast(double[,] equity, double reliability, double maximumLoss, double minimumCoefficientValue)
        {
            CalculateLinearValidation(reliability, maximumLoss);

            double[,] deltaEquity = NumericalMethods.CalculateAbsoluteVariation(equity);
            double[,] sigma       = Statistics.CalculateCovarianceMatrix(deltaEquity);
            Log.Technical("sigma = ", MathFormatProvider.InputStringFromTable(sigma));
            double[] profit = Statistics.CalculateAverage(deltaEquity);
            Log.Technical("sigma = ", MathFormatProvider.InputStringFromData(profit));
            int n = profit.Length;

            Portfolio result = new Portfolio();

            result.Coefficients = new double[n];
            result.When         = double.NaN;
            bool[] zeros = new bool[n];

            bool status = false;

            do
            {
                status = CalculateLinearFastInternal(result, zeros, sigma, profit, reliability, maximumLoss, minimumCoefficientValue, FastAbsoluteMinimalThreshold);
            } while (!status);
            return(result);
        }
Esempio n. 2
0
        public static Portfolio CalculateLinearMarginBalance(PortfolioInput input, Vector[] balance)
        {
            CalculateLinearValidation(input.Reliability, input.MaximumLoss);

            if (input.InitialDeposit <= input.MaximumLoss)
            {
                string st = string.Format("Initial deposit = {0} should be more than maximum loss = {1}", input.InitialDeposit, input.MaximumLoss);
                throw new ArgumentException();
            }
            if (input.MarginLevelThreshold <= 0)
            {
                string st = string.Format("Margin level = {0}, but must be positive", input.MarginLevelThreshold);
                throw new ArgumentException();
            }

            double marginThreshold = (input.InitialDeposit - input.MaximumLoss) / input.MarginLevelThreshold;

            double[,] deltaEquity = NumericalMethods.CalculateAbsoluteVariation(input.Equity);
            double[,] sigma       = Statistics.CalculateCovarianceMatrix(deltaEquity);

            int count = sigma.GetLength(0);

            for (int i = 0; i < count; ++i)
            {
                for (int j = 1 + i; j < count; ++j)
                {
                    sigma[i, j] = 0;
                    sigma[j, i] = 0;
                }
            }
            double[] profit = Statistics.CalculateAverage(deltaEquity);

            Log.Technical("sigma = {0}", MathFormatProvider.InputStringFromTable(sigma));
            Log.Technical("profit = {0}", MathFormatProvider.InputStringFromData(profit));
            int n = profit.Length;

            double[] m = input.Margin.MaximumByRow();

            Portfolio result = new Portfolio();

            result.Coefficients = new double[n];
            result.When         = double.NaN;
            bool[] zeros = new bool[n];

            Vector[] _balance = new Vector[balance.Length - 1];
            for (int index = 1; index < balance.Length; ++index)
            {
                _balance[index - 1] = balance[index] - balance[0];
            }
            double[] margin = input.Margin.MaximumByRow();
            bool     status = false;

            do
            {
                status = CalculateLinearMarginBalanceInternal(result, zeros, sigma, profit, margin, input, _balance);
            } while (!status);
            return(result);
        }
Esempio n. 3
0
        public static Portfolio CalculateLinearFast(double[,] equity, double[,] margin, double initialDeposit, double reliability, double maximumLoss,
                                                    double marginLevel, double minimumCoefficientValue)
        {
            CalculateLinearValidation(reliability, maximumLoss);

            if (maximumLoss <= 0)
            {
                string st = string.Format("maximumLoss = {0}, but must be positive", maximumLoss);
                throw new ArgumentException();
            }
            if (initialDeposit <= maximumLoss)
            {
                string st = string.Format("Initial deposit = {0} should be more than maximum loss = {1}", initialDeposit, maximumLoss);
                throw new ArgumentException();
            }
            if (marginLevel <= 0)
            {
                string st = string.Format("Margin level = {0}, but must be positive", marginLevel);
                throw new ArgumentException();
            }

            double marginThreshold = (initialDeposit - maximumLoss) / marginLevel;

            double[,] deltaEquity = NumericalMethods.CalculateAbsoluteVariation(equity);
            double[,] sigma       = Statistics.CalculateCovarianceMatrix(deltaEquity);
            double[] profit = Statistics.CalculateAverage(deltaEquity);

            Log.Technical("sigma = {0}", MathFormatProvider.InputStringFromTable(sigma));
            Log.Technical("profit = {0}", MathFormatProvider.InputStringFromData(profit));
            int n = profit.Length;

            double[] m = margin.MaximumByRow();

            Portfolio result = new Portfolio();

            result.Coefficients = new double[n];
            result.When         = double.NaN;
            bool[] zeros = new bool[n];


            bool status = false;

            do
            {
                status = CalculateLinearFastInternal(result, zeros, sigma, profit, m, reliability, maximumLoss, minimumCoefficientValue, marginThreshold);
            } while (!status);
            return(result);
        }
Esempio n. 4
0
        public void Add(string name, double[] values)
        {
            string st = MathFormatProvider.InputStringFromData(values);

            this[name] = st;
        }