suradi
06 Feb 2018, 12:31

This should get you started with perceptrons :)

 private double perceptron1()
        {
            int[,] input = new int[,] 
            {
                {
                    1,
                    0
                },
                {
                    1,
                    1
                },
                {
                    0,
                    1
                },
                {
                    0,
                    0
                }
            };

            int[] outputs = 
            {
                0,
                1,
                0,
                0
            };


            Random r = new Random();

            double[] weights = 
            {
                r.NextDouble(),
                r.NextDouble(),
                r.NextDouble()
            };
            double learningRate = 500;
            double totalError = 1;
            int last = MarketSeries.Close.Count - 1;
            while (totalError > 0.2)
            {
                totalError = 0;
                for (int i = 0; i < 4; i++)
                {

                    int output = calculateOutput1(input[i, 0], input[i, 1], weights);
                    int error = outputs[i] - output;

                    weights[0] += learningRate * error * input[i, 0];
                    weights[1] += learningRate * error * input[i, 1];
                    weights[2] += learningRate * error * 1;

                    totalError += Math.Abs(error);

                }


            }
            //macd.Histogram
            double a1 = macd.Histogram[last - 1];
            double a2 = macd.Histogram[last - 1 - 1];
            double a3 = macd.Histogram[last - 1 - 1 * 2];
            double a4 = macd.Histogram[last - 1 - 1 * 3];
            double sum = (weights[0] * a1) + (weights[1] * a2) + (weights[0] * a3) + (weights[1] * a4);
            return (sum >= 0) ? 1 : 0;



        }

        private static int calculateOutput1(double a1, double a2, double[] weights)
        {

            double sum = a1 * weights[0] + a2 * weights[1] + 1 * weights[2];
            return (sum >= 0) ? 1 : 0;
        }

suradi
21 Jan 2018, 13:17

RE:

Thank you! This should get me started

Panagiotis Charalampous said:

Hi Surady,

See below a very simple example on how to calculate your average equity with samples taken on each bar change.

using System;
using System.Linq;
using cAlgo.API;
using cAlgo.API.Indicators;
using cAlgo.API.Internals;
using cAlgo.Indicators;

namespace cAlgo
{
    [Robot(TimeZone = TimeZones.UTC, AccessRights = AccessRights.None)]
    public class AverageEquity : Robot
    {
        [Parameter(DefaultValue = 0.0)]
        public double Parameter { get; set; }

        private double _equity;
        private double _periodCount;

        protected override void OnStart()
        {
            ExecuteMarketOrder(TradeType.Buy, Symbol, 10000);
        }

        protected override void OnBar()
        {
            _equity += Account.Equity;
            _periodCount++;
            Print("Average Equity:" + (_equity / _periodCount));
        }

        protected override void OnStop()
        {
            // Put your deinitialization logic here
        }
    }
}

If you need something more complicated or any professional help in developing your cBot, you can post a Job or contact a professional Consultant.

Best Regards,

Panagiotis

suradi
23 Feb 2017, 13:06 ( Updated at: 21 Dec 2023, 09:20 )

RE:

trend_meanreversion said:

This week was definitely tough for strategy but despite having drawdowns , it came victorious !! 

Target hit for the week already ( 500$ or 10% ) :)

Next week or probably next , i am going live .

Looks great trend. Will you be posting a copy of your martingale cbot so we can test it out ? :)

suradi
12 Dec 2016, 06:56

Have you tried putting your execution code in the onBar() method ?