Time Series Moving Average

whis.gg
27 Feb 2017, 02:34

Hi, Time Series Moving Average is equal to Linear Regression Forecast. The cAlgo platform calculates it by multiplying Linear Regression Slope with Period plus Linear Regression Intercept. Here's is better solution that gives you same result.

using cAlgo.API;

namespace cAlgo
{
    [Indicator(IsOverlay = true, TimeZone = TimeZones.UTC, AccessRights = AccessRights.None)]
    public class LinearRegression : Indicator
    {
        [Parameter()]
        public DataSeries Source { get; set; }

        [Parameter(DefaultValue = 14)]
        public int Period { get; set; }

        [Output("Main")]
        public IndicatorDataSeries Result { get; set; }

        public override void Calculate(int index)
        {
            double sumX = 0, sumY = 0, sumXY = 0, sumXPower = 0;

            for (int i = 0; i < Period; i++)
            {
                sumXPower += i * i;
                sumX += i;
                sumY += Source[index - i];
                sumXY += i * Source[index - i];
            }

            Result[index] = (sumXPower * sumY - sumX * sumXY) / (sumXPower * Period - sumX * sumX);
        }
    }
}

jaredthirsk
27 Feb 2017, 09:35

RE:

tmc. said:

Hi, Time Series Moving Average is equal to Linear Regression Forecast. The cAlgo platform calculates it by multiplying Linear Regression Slope with Period plus Linear Regression Intercept. Here's is better solution that gives you same result.

Awesome, thanks!

Vidya is the other moving average I was wondering about.  Do you know the best way to calculate that?

whis.gg
27 Feb 2017, 12:19

Not sure if it's the best way but it's the one cAlgo uses.

using System;
using cAlgo.API;

namespace cAlgo
{
    [Indicator(IsOverlay = true, TimeZone = TimeZones.UTC, AccessRights = AccessRights.None)]
    public class Vidya : Indicator
    {
        [Parameter()]
        public DataSeries Source { get; set; }

        [Parameter("Period", DefaultValue = 14)]
        public int Period { get; set; }

        [Parameter("Sigma", DefaultValue = 0.65, MinValue = 0.1, MaxValue = 0.95)]
        public double Sigma { get; set; }

        [Output("Main")]
        public IndicatorDataSeries Result { get; set; }

        public override void Calculate(int index)
        {
            double num = this.Result[index - 1];

            if (double.IsNaN(num))
            {
                num = Source[index - 1];
            }
            double num2 = Sigma * Cmo(index);

            Result[index] = (1.0 - num2) * num + num2 * Source[index];
        }

        private double Cmo(int index)
        {
            double num = 0.0;
            double num2 = 0.0;

            for (int i = 0; i < Period; i++)
            {
                double num3 = Source[index - i] - Source[index - i - 1];

                if (num3 > 0.0)
                {
                    num += num3;
                }
                else
                {
                    num2 += -num3;
                }
            }

            if (num + num2 == 0.0)
            {
                return 0.0;
            }

            return Math.Abs((num - num2) / (num + num2));
        }
    }
}