Skip to content

LinearRegressionIntercept

Summary

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

Remarks

Linear regression is a statistical tool used to predict the future from past data.

Signature 

1
public abstract interface LinearRegressionIntercept

Namespace

cAlgo.API.Indicators

Examples

1
2
3
4
5
6
7
 [Parameter("Period", DefaultValue = 14)]
    public int Period { get; set; }
    protected override void OnStart()
 {
     // initialize a new instance of LinearRegressionIntercept indicator class
        _linearRegressionIntercept = Indicators.LinearRegressionIntercept(MarketSeries.Close, Period);
    }

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
 using cAlgo.API;
 using cAlgo.API.Indicators;
 using cAlgo.API.Internals;
 namespace cAlgo.Robots
 {
     // This sample cBot shows how to use the Linear Regression Intercept indicator
     [Robot(TimeZone = TimeZones.UTC, AccessRights = AccessRights.None)]
     public class LinearRegressionInterceptSample : Robot
     {
         private double _volumeInUnits;
         private LinearRegressionIntercept _linearRegressionIntercept;
         [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);
             _linearRegressionIntercept = Indicators.LinearRegressionIntercept(Bars.ClosePrices, 20);
         }
         protected override void OnBar()
         {
             if (Bars.ClosePrices.Last(1) > _linearRegressionIntercept.Result.Last(1) && Bars.ClosePrices.Last(2) <= _linearRegressionIntercept.Result.Last(2))
             {
                 ClosePositions(TradeType.Sell);
                 ExecuteMarketOrder(TradeType.Buy, SymbolName, _volumeInUnits, Label, StopLossInPips, TakeProfitInPips);
             }
             else if (Bars.ClosePrices.Last(1) < _linearRegressionIntercept.Result.Last(1) && Bars.ClosePrices.Last(2) >= _linearRegressionIntercept.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);
             }
         }
     }
 }

Properties

Result

Summary

The Result Series of the Linear Regression Intercept Indicator

Signature 

1
public abstract IndicatorDataSeries Result {get;}

Return Value

IndicatorDataSeries

Examples

1
2
3
4
5
6
7
    public override void Calculate(int index)
    {
      // Result of _linearRegressionIntercept at the current index
      double result = _linearRegressionIntercept.Result[index];
      // Print the current result to the log
        Print("Linear Regression Intercept at the current index is = {0}", result);
    }