Supported Indicators

Vortex

Introduction

This indicator represents the Vortex Indicator, which identifies the start and continuation of market trends. It includes components that capture positive (upward) and negative (downward) trend movements. This indicator compares the ranges within the current period to previous periods to calculate upward and downward movement trends.

To view the implementation of this indicator, see the LEAN GitHub repository.

Using VTX Indicator

To create an automatic indicators for Vortex, call the VTX helper method from the QCAlgorithm class. The VTX method creates a Vortex 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 Initializeinitialize method.

public class VortexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Vortex _vtx;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _vtx = VTX(_symbol, 14);
    }

    public override void OnData(Slice data)
    {
        if (_vtx.IsReady)
        {
            // The current value of _vtx is represented by itself (_vtx)
            // or _vtx.Current.Value
            Plot("Vortex", "vtx", _vtx);
            // Plot all properties of vtx
            Plot("Vortex", "plusvortex", _vtx.PlusVortex);
            Plot("Vortex", "minusvortex", _vtx.MinusVortex);
        }
    }
}
class VortexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._vtx = self.vtx(self._symbol, 14)

    def on_data(self, slice: Slice) -> None:
        if self._vtx.is_ready:
            # The current value of self._vtx is represented by self._vtx.current.value
            self.plot("Vortex", "vtx", self._vtx.current.value)
            # Plot all attributes of self._vtx
            self.plot("Vortex", "plus_vortex", self._vtx.plus_vortex.current.value)
            self.plot("Vortex", "minus_vortex", self._vtx.minus_vortex.current.value)

The following reference table describes the VTX method:

vtx(symbol, period, resolution=None, selector=None)[source]

Creates a new Vortex indicator for the symbol. The indicator will be automatically updated on the given resolution.

Parameters:
  • symbol (Symbol) — The symbol whose VWMA we want
  • period (int) — The smoothing period used to smooth the computed VWMA values
  • resolution (Resolution, optional) — The resolution
  • selector (Callable[IBaseData, IBaseDataBar], optional) — Selects a value from the BaseData to send into the indicator, if null defaults to casting the input value to a TradeBar
Returns:

A new Vortex indicator with the specified smoothing period

Return type:

Vortex

VTX(symbol, period, resolution=None, selector=None)[source]

Creates a new Vortex indicator for the symbol. The indicator will be automatically updated on the given resolution.

Parameters:
  • symbol (Symbol) — The symbol whose VWMA we want
  • period (Int32) — The smoothing period used to smooth the computed VWMA values
  • resolution (Resolution, optional) — The resolution
  • selector (Func<IBaseData, IBaseDataBar>, optional) — Selects a value from the BaseData to send into the indicator, if null defaults to casting the input value to a TradeBar
Returns:

A new Vortex indicator with the specified smoothing period

Return type:

Vortex

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.

For more information about the selector argument, see Alternative Price Fields.

For more information about plotting indicators, see Plotting Indicators.

You can manually create a Vortex 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 Updateupdate method with a TradeBar or QuoteBar. The indicator will only be ready after you prime it with enough data.

public class VortexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Vortex _vtx;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _vtx = new Vortex(14);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _vtx.Update(bar);
        }
   
        if (_vtx.IsReady)
        {
            // The current value of _vtx is represented by itself (_vtx)
            // or _vtx.Current.Value
            Plot("Vortex", "vtx", _vtx);
            // Plot all properties of vtx
            Plot("Vortex", "plusvortex", _vtx.PlusVortex);
            Plot("Vortex", "minusvortex", _vtx.MinusVortex);
        }
    }
}
class VortexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._vtx = Vortex(14)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._vtx.update(bar)
        if self._vtx.is_ready:
            # The current value of self._vtx is represented by self._vtx.current.value
            self.plot("Vortex", "vtx", self._vtx.current.value)
            # Plot all attributes of self._vtx
            self.plot("Vortex", "plus_vortex", self._vtx.plus_vortex.current.value)
            self.plot("Vortex", "minus_vortex", self._vtx.minus_vortex.current.value)

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

public class VortexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Vortex _vtx;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _vtx = new Vortex(14);
        RegisterIndicator(_symbol, _vtx, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_vtx.IsReady)
        {
            // The current value of _vtx is represented by itself (_vtx)
            // or _vtx.Current.Value
            Plot("Vortex", "vtx", _vtx);
            // Plot all properties of vtx
            Plot("Vortex", "plusvortex", _vtx.PlusVortex);
            Plot("Vortex", "minusvortex", _vtx.MinusVortex);
        }
    }
}
class VortexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._vtx = Vortex(14)
        self.register_indicator(self._symbol, self._vtx, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self._vtx.is_ready:
            # The current value of self._vtx is represented by self._vtx.current.value
            self.plot("Vortex", "vtx", self._vtx.current.value)
            # Plot all attributes of self._vtx
            self.plot("Vortex", "plus_vortex", self._vtx.plus_vortex.current.value)
            self.plot("Vortex", "minus_vortex", self._vtx.minus_vortex.current.value)

The following reference table describes the Vortex constructor:

Vortex

class QuantConnect.Indicators.Vortex[source]

Represents the Vortex Indicator, which identifies the start and continuation of market trends. It includes components that capture positive (upward) and negative (downward) trend movements. This indicator compares the ranges within the current period to previous periods to calculate upward and downward movement trends.

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets all indicators and internal state.

to_detailed_string()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

str

update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (datetime)
  • value (float)
Return type:

bool

update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

bool

property consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet[IDataConsolidator]

property current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property is_ready

Indicates whether this indicator is fully ready and all buffers have been filled.

Returns:

Indicates whether this indicator is fully ready and all buffers have been filled.

Return type:

bool

property item

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

property minus_vortex

Gets the Negative Vortex Indicator, which reflects negative trend movements.

Returns:

Gets the Negative Vortex Indicator, which reflects negative trend movements.

Return type:

IndicatorBase[IndicatorDataPoint]

property name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

str

property plus_vortex

Gets the Positive Vortex Indicator, which reflects positive trend movements.

Returns:

Gets the Positive Vortex Indicator, which reflects positive trend movements.

Return type:

IndicatorBase[IndicatorDataPoint]

property previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property warm_up_period

The minimum number of samples needed for the indicator to be ready and provide reliable values.

Returns:

The minimum number of samples needed for the indicator to be ready and provide reliable values.

Return type:

int

property window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow[IndicatorDataPoint]

Vortex

class QuantConnect.Indicators.Vortex[source]

Represents the Vortex Indicator, which identifies the start and continuation of market trends. It includes components that capture positive (upward) and negative (downward) trend movements. This indicator compares the ranges within the current period to previous periods to calculate upward and downward movement trends.

GetEnumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

Reset()

Resets all indicators and internal state.

ToDetailedString()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

String

Update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (DateTime)
  • value (decimal)
Return type:

Boolean

Update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

Boolean

property Consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet<IDataConsolidator>

property Current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property IsReady

Indicates whether this indicator is fully ready and all buffers have been filled.

Returns:

Indicates whether this indicator is fully ready and all buffers have been filled.

Return type:

bool

property MinusVortex

Gets the Negative Vortex Indicator, which reflects negative trend movements.

Returns:

Gets the Negative Vortex Indicator, which reflects negative trend movements.

Return type:

IndicatorBase<IndicatorDataPoint>

property Name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

string

property PlusVortex

Gets the Positive Vortex Indicator, which reflects positive trend movements.

Returns:

Gets the Positive Vortex Indicator, which reflects positive trend movements.

Return type:

IndicatorBase<IndicatorDataPoint>

property Previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property Samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property WarmUpPeriod

The minimum number of samples needed for the indicator to be ready and provide reliable values.

Returns:

The minimum number of samples needed for the indicator to be ready and provide reliable values.

Return type:

Int32

property Window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow<IndicatorDataPoint>

property [System.Int32]

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

Visualization

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

Vortex line plot.

Indicator History

To get the historical data of the Vortex indicator, call the IndicatorHistoryself.indicator_history method. This method resets your indicator, makes a history request, and updates the indicator with the historical data. Just like with regular history requests, the IndicatorHistoryindicator_history method supports time periods based on a trailing number of bars, a trailing period of time, or a defined period of time. If you don't provide a resolution argument, it defaults to match the resolution of the security subscription. 

public class VortexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        var vtx = VTX(_symbol, 14);
        var countIndicatorHistory = IndicatorHistory(vtx, _symbol, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(vtx, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(vtx, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
    }
}
class VortexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        vtx = self.vtx(self._symbol, 14)
        count_indicator_history = self.indicator_history(vtx, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(vtx, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(vtx, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)

To make the IndicatorHistoryindicator_history method update the indicator with an alternative price field instead of the close (or mid-price) of each bar, pass a selector argument.

var indicatorHistory = IndicatorHistory(vtx, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(vtx, 100, Resolution.MINUTE, lambda bar: bar.high)
indicator_history_df = indicator_history.data_frame

If you already have a list of Slice objects, you can pass them to the IndicatorHistoryindicator_history method to avoid the internal history request.

var history = History(_symbol, 100, Resolution.Minute);
var historyIndicatorHistory = IndicatorHistory(vtx, history);

To access the properties of the indicator history, invoke the property of each IndicatorDataPoint object.index the DataFrame with the property name.

var plusvortex = indicatorHistory.Select(x => ((dynamic)x).PlusVortex).ToList();
var minusvortex = indicatorHistory.Select(x => ((dynamic)x).MinusVortex).ToList();

// Alternative way
// var plusvortex = indicatorHistory.Select(x => x["plusvortex"]).ToList();
// var minusvortex = indicatorHistory.Select(x => x["minusvortex"]).ToList();

plus_vortex = indicator_history_df["plus_vortex"]
minus_vortex = indicator_history_df["minus_vortex"]

# Alternative way
# plus_vortex = indicator_history_df.plus_vortex
# minus_vortex = indicator_history_df.minus_vortex

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