LinearRegressionForecast


Summary

Linear Regression Forecast is one of the indicators calculated by the Linear Regression approach.

Remarks

The Linear Regression Forecast is used for identifying trends and trend direction, and shows the statistical trend of a financial instrument over a specified time period. The calculation uses a Linear Regression Line.

Syntax

public interface LinearRegressionForecast

Members

NameTypeSummary
Result PropertyThe Result Series of the Linear Regression Forecast Indicator

Example 1

private LinearRegressionForecast _linearRegressionForecast;
[Parameter("Period", DefaultValue = 14)]
public int Period { get; set; }
protected override void Initialize()
{
    // initialize a new instance of LinearRegressionForecastIndicator class
    _linearRegressionForecast = Indicators.LinearRegressionForecast(MarketSeries.Close, Period);
}

Example 2

using cAlgo.API;
using cAlgo.API.Indicators;
using cAlgo.API.Internals;
namespace cAlgo.Robots
{
    // This sample cBot shows how to use the Linear Regression Forecast indicator
    [Robot(TimeZone = TimeZones.UTC, AccessRights = AccessRights.None)]
    public class LinearRegressionForecastSample : Robot
    {
        private double _volumeInUnits;
        private LinearRegressionForecast _linearRegressionForecast;
        [Parameter("Volume (Lots)", DefaultValue = 0.01)]
        public double VolumeInLots { get; set; }
        [Parameter("Stop Loss (Pips)", DefaultValue = 10)]
        public double StopLossInPips { get; set; }
        [Parameter("Take Profit (Pips)", DefaultValue = 10)]
        public double TakeProfitInPips { get; set; }
        [Parameter("Label", DefaultValue = "Sample")]
        public string Label { get; set; }
        public Position[] BotPositions
        {
            get
            {
                return Positions.FindAll(Label);
            }
        }
        protected override void OnStart()
        {
            _volumeInUnits = Symbol.QuantityToVolumeInUnits(VolumeInLots);
            _linearRegressionForecast = Indicators.LinearRegressionForecast(Bars.ClosePrices, 20);
        }
        protected override void OnBar()
        {
            if (Bars.ClosePrices.Last(1) > _linearRegressionForecast.Result.Last(1) && Bars.ClosePrices.Last(2) <= _linearRegressionForecast.Result.Last(2))
            {
                ClosePositions(TradeType.Sell);
                ExecuteMarketOrder(TradeType.Buy, SymbolName, _volumeInUnits, Label, StopLossInPips, TakeProfitInPips);
            }
            else if (Bars.ClosePrices.Last(1) < _linearRegressionForecast.Result.Last(1) && Bars.ClosePrices.Last(2) >= _linearRegressionForecast.Result.Last(2))
            {
                ClosePositions(TradeType.Buy);
                ExecuteMarketOrder(TradeType.Sell, SymbolName, _volumeInUnits, Label, StopLossInPips, TakeProfitInPips);
            }
        }
        private void ClosePositions(TradeType tradeType)
        {
            foreach (var position in BotPositions)
            {
                if (position.TradeType != tradeType) continue;
                ClosePosition(position);
            }
        }
    }
}
Reference