# Supported Indicators

## Average Directional Index

### Introduction

This indicator computes Average Directional Index which measures trend strength without regard to trend direction. Firstly, it calculates the Directional Movement and the True Range value, and then the values are accumulated and smoothed using a custom smoothing method proposed by Wilder. For an n period smoothing, 1/n of each period's value is added to the total period. From these accumulated values we are therefore able to derived the 'Positive Directional Index' (+DI) and 'Negative Directional Index' (-DI) which is used to calculate the Average Directional Index. Computation source: https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:average_directional_index_adx

To create an automatic indicators for AverageDirectionalIndex, call the ADX helper method from the QCAlgorithm class. The ADX method creates a AverageDirectionalIndex object, hooks it up for automatic updates, and returns it so you can used it in your algorithm. In most cases, you should call the helper method in the Initialize method.

public class AverageDirectionalIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;

public override void Initialize()
{
}

public override void OnData(Slice data)
{
{
}
}
}
class AverageDirectionalIndexAlgorithm(QCAlgorithm):
def Initialize(self) -> None:

def OnData(self, slice: Slice) -> None:


The following reference table describes the ADX method:

            AverageDirectionalIndex QuantConnect.Algorithm.QCAlgorithm.ADX (
Symbol                                symbol,
Int32                                 period,
*Nullable<Resolution>           resolution,
*Func<IBaseData, IBaseDataBar>  selector
)


Creates a new Average Directional Index indicator. The indicator will be automatically updated on the given resolution.

If you don't provide a resolution, it defaults to the security resolution. If you provide a resolution, it must be greater than or equal to the resolution of the security. For instance, if you subscribe to hourly data for a security, you should update its indicator with data that spans 1 hour or longer.

You can manually create a AverageDirectionalIndex indicator, so it doesn't automatically update. Manual indicators let you update their values with any data you choose.

Updating your indicator manually enables you to control when the indicator is updated and what data you use to update it. To manually update the indicator, call the Update method with a TradeBar, or QuoteBar. The indicator will only be ready after you prime it with enough data.

public class AverageDirectionalIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;

public override void Initialize()
{
}

public override void OnData(Slice data)
{
if (data.Bars.TryGeValue(_symbol, out var bar))
{
}

{
}
}
}
class AverageDirectionalIndexAlgorithm(QCAlgorithm):
def Initialize(self) -> None:

def OnData(self, slice: Slice) -> None:
bar = data.Bars.get(self.symbol)
if bar:



To register a manual indicator for automatic updates with the security data, call the RegisterIndicator method.

public class AverageDirectionalIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;

public override void Initialize()
{
}

public override void OnData(Slice data)
{
{
}
}
}
class AverageDirectionalIndexAlgorithm(QCAlgorithm):
def Initialize(self) -> None:

def OnData(self, slice: Slice) -> None:


The following reference table describes the AverageDirectionalIndex constructor:

### AverageDirectionalIndex()1/2

            AverageDirectionalIndex QuantConnect.Indicators.AverageDirectionalIndex (
int  period
)


Initializes a new instance of the AverageDirectionalInde class.

### AverageDirectionalIndex()2/2

            AverageDirectionalIndex QuantConnect.Indicators.AverageDirectionalIndex (
string  name,
int     period
)


Initializes a new instance of the AverageDirectionalInde class.

### Visualization

The following image shows plot values of selected properties of AverageDirectionalIndex using the plotly library.

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