Supported Indicators

Moving Average Convergence Divergence

Introduction

This indicator creates two moving averages defined on a base indicator and produces the difference between the fast and slow averages.

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

Using MACD Indicator

To create an automatic indicators for MovingAverageConvergenceDivergence, call the MACD helper method from the QCAlgorithm class. The MACD method creates a MovingAverageConvergenceDivergence 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 MovingAverageConvergenceDivergenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private MovingAverageConvergenceDivergence _macd;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _macd = MACD(_symbol, 12, 26, 9, MovingAverageType.Exponential);
    }

    public override void OnData(Slice data)
    {
        if (_macd.IsReady)
        {
            // The current value of _macd is represented by itself (_macd)
            // or _macd.Current.Value
            Plot("MovingAverageConvergenceDivergence", "macd", _macd);
            // Plot all properties of macd
            Plot("MovingAverageConvergenceDivergence", "fast", _macd.Fast);
            Plot("MovingAverageConvergenceDivergence", "slow", _macd.Slow);
            Plot("MovingAverageConvergenceDivergence", "signal", _macd.Signal);
            Plot("MovingAverageConvergenceDivergence", "histogram", _macd.Histogram);
        }
    }
}
class MovingAverageConvergenceDivergenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._macd = self.macd(self._symbol, 12, 26, 9, MovingAverageType.Exponential)

    def on_data(self, slice: Slice) -> None:
        if self._macd.is_ready:
            # The current value of self._macd is represented by self._macd.current.value
            self.plot("MovingAverageConvergenceDivergence", "macd", self._macd.current.value)
            # Plot all attributes of self._macd
            self.plot("MovingAverageConvergenceDivergence", "fast", self._macd.fast.current.value)
            self.plot("MovingAverageConvergenceDivergence", "slow", self._macd.slow.current.value)
            self.plot("MovingAverageConvergenceDivergence", "signal", self._macd.signal.current.value)
            self.plot("MovingAverageConvergenceDivergence", "histogram", self._macd.histogram.current.value)

The following reference table describes the MACD method:

macd(symbol, fast_period, slow_period, signal_period, type=1, resolution=None, selector=None)[source]

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

Parameters:
  • symbol (Symbol) — The symbol whose MACD we want
  • fast_period (int) — The period for the fast moving average
  • slow_period (int) — The period for the slow moving average
  • signal_period (int) — The period for the signal moving average
  • type (MovingAverageType, optional) — The type of moving average to use for the MACD
  • resolution (Resolution, optional) — The resolution
  • selector (Callable[IBaseData, float], optional) — x.Value)
Returns:

The moving average convergence divergence between the fast and slow averages

Return type:

MovingAverageConvergenceDivergence

MACD(symbol, fastPeriod, slowPeriod, signalPeriod, type=1, resolution=None, selector=None)[source]

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

Parameters:
  • symbol (Symbol) — The symbol whose MACD we want
  • fastPeriod (Int32) — The period for the fast moving average
  • slowPeriod (Int32) — The period for the slow moving average
  • signalPeriod (Int32) — The period for the signal moving average
  • type (MovingAverageType, optional) — The type of moving average to use for the MACD
  • resolution (Resolution, optional) — The resolution
  • selector (Func<IBaseData, Decimal>, optional) — x.Value)
Returns:

The moving average convergence divergence between the fast and slow averages

Return type:

MovingAverageConvergenceDivergence

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 MovingAverageConvergenceDivergence 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 time/number pair or an IndicatorDataPoint. The indicator will only be ready after you prime it with enough data.

public class MovingAverageConvergenceDivergenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private MovingAverageConvergenceDivergence _macd;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _macd = new MovingAverageConvergenceDivergence(12, 26, 9, MovingAverageType.Exponential);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _macd.Update(bar.EndTime, bar.Close);
        }
   
        if (_macd.IsReady)
        {
            // The current value of _macd is represented by itself (_macd)
            // or _macd.Current.Value
            Plot("MovingAverageConvergenceDivergence", "macd", _macd);
            // Plot all properties of macd
            Plot("MovingAverageConvergenceDivergence", "fast", _macd.Fast);
            Plot("MovingAverageConvergenceDivergence", "slow", _macd.Slow);
            Plot("MovingAverageConvergenceDivergence", "signal", _macd.Signal);
            Plot("MovingAverageConvergenceDivergence", "histogram", _macd.Histogram);
        }
    }
}
class MovingAverageConvergenceDivergenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._macd = MovingAverageConvergenceDivergence(12, 26, 9, MovingAverageType.Exponential)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._macd.update(bar.EndTime, bar.Close)
        if self._macd.is_ready:
            # The current value of self._macd is represented by self._macd.current.value
            self.plot("MovingAverageConvergenceDivergence", "macd", self._macd.current.value)
            # Plot all attributes of self._macd
            self.plot("MovingAverageConvergenceDivergence", "fast", self._macd.fast.current.value)
            self.plot("MovingAverageConvergenceDivergence", "slow", self._macd.slow.current.value)
            self.plot("MovingAverageConvergenceDivergence", "signal", self._macd.signal.current.value)
            self.plot("MovingAverageConvergenceDivergence", "histogram", self._macd.histogram.current.value)

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

public class MovingAverageConvergenceDivergenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private MovingAverageConvergenceDivergence _macd;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _macd = new MovingAverageConvergenceDivergence(12, 26, 9, MovingAverageType.Exponential);
        RegisterIndicator(_symbol, _macd, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_macd.IsReady)
        {
            // The current value of _macd is represented by itself (_macd)
            // or _macd.Current.Value
            Plot("MovingAverageConvergenceDivergence", "macd", _macd);
            // Plot all properties of macd
            Plot("MovingAverageConvergenceDivergence", "fast", _macd.Fast);
            Plot("MovingAverageConvergenceDivergence", "slow", _macd.Slow);
            Plot("MovingAverageConvergenceDivergence", "signal", _macd.Signal);
            Plot("MovingAverageConvergenceDivergence", "histogram", _macd.Histogram);
        }
    }
}
class MovingAverageConvergenceDivergenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._macd = MovingAverageConvergenceDivergence(12, 26, 9, MovingAverageType.Exponential)
        self.register_indicator(self._symbol, self._macd, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self._macd.is_ready:
            # The current value of self._macd is represented by self._macd.current.value
            self.plot("MovingAverageConvergenceDivergence", "macd", self._macd.current.value)
            # Plot all attributes of self._macd
            self.plot("MovingAverageConvergenceDivergence", "fast", self._macd.fast.current.value)
            self.plot("MovingAverageConvergenceDivergence", "slow", self._macd.slow.current.value)
            self.plot("MovingAverageConvergenceDivergence", "signal", self._macd.signal.current.value)
            self.plot("MovingAverageConvergenceDivergence", "histogram", self._macd.histogram.current.value)

The following reference table describes the MovingAverageConvergenceDivergence constructor:

MovingAverageConvergenceDivergence

class QuantConnect.Indicators.MovingAverageConvergenceDivergence[source]

This indicator creates two moving averages defined on a base indicator and produces the difference between the fast and slow averages.

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets this indicator to its initial 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 fast

Gets the fast average indicator

Returns:

Gets the fast average indicator

Return type:

IndicatorBase[IndicatorDataPoint]

property histogram

Developed by Thomas Aspray in 1986, the MACD-Histogram measures the distance between MACD and its signal line, is an oscillator that fluctuates above and below the zero line. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD.

Returns:

Developed by Thomas Aspray in 1986, the MACD-Histogram measures the distance between MACD and its signal line, is an oscillator that fluctuates above and below the zero line. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD.

Return type:

IndicatorBase[IndicatorDataPoint]

property is_ready

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

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 name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

str

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 signal

Gets the signal of the MACD

Returns:

Gets the signal of the MACD

Return type:

IndicatorBase[IndicatorDataPoint]

property slow

Gets the slow average indicator

Returns:

Gets the slow average indicator

Return type:

IndicatorBase[IndicatorDataPoint]

property warm_up_period

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

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]

MovingAverageConvergenceDivergence

class QuantConnect.Indicators.MovingAverageConvergenceDivergence[source]

This indicator creates two moving averages defined on a base indicator and produces the difference between the fast and slow averages.

GetEnumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

Reset()

Resets this indicator to its initial 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 Fast

Gets the fast average indicator

Returns:

Gets the fast average indicator

Return type:

IndicatorBase<IndicatorDataPoint>

property Histogram

Developed by Thomas Aspray in 1986, the MACD-Histogram measures the distance between MACD and its signal line, is an oscillator that fluctuates above and below the zero line. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD.

Returns:

Developed by Thomas Aspray in 1986, the MACD-Histogram measures the distance between MACD and its signal line, is an oscillator that fluctuates above and below the zero line. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD.

Return type:

IndicatorBase<IndicatorDataPoint>

property IsReady

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

Return type:

bool

property Name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

string

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 Signal

Gets the signal of the MACD

Returns:

Gets the signal of the MACD

Return type:

IndicatorBase<IndicatorDataPoint>

property Slow

Gets the slow average indicator

Returns:

Gets the slow average indicator

Return type:

IndicatorBase<IndicatorDataPoint>

property WarmUpPeriod

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

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 MovingAverageConvergenceDivergence using the plotly library.

MovingAverageConvergenceDivergence line plot.

Indicator History

To get the historical data of the MovingAverageConvergenceDivergence 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 MovingAverageConvergenceDivergenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        var macd = MACD(_symbol, 12, 26, 9, MovingAverageType.Exponential);
        var countIndicatorHistory = IndicatorHistory(macd, _symbol, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(macd, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(macd, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
    }
}
class MovingAverageConvergenceDivergenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        macd = self.macd(self._symbol, 12, 26, 9, MovingAverageType.Exponential)
        count_indicator_history = self.indicator_history(macd, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(macd, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(macd, 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(macd, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(macd, 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(macd, history);

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

var fast = indicatorHistory.Select(x => ((dynamic)x).Fast).ToList();
var slow = indicatorHistory.Select(x => ((dynamic)x).Slow).ToList();
var signal = indicatorHistory.Select(x => ((dynamic)x).Signal).ToList();
var histogram = indicatorHistory.Select(x => ((dynamic)x).Histogram).ToList();

// Alternative way
// var fast = indicatorHistory.Select(x => x["fast"]).ToList();
// var slow = indicatorHistory.Select(x => x["slow"]).ToList();
// var signal = indicatorHistory.Select(x => x["signal"]).ToList();
// var histogram = indicatorHistory.Select(x => x["histogram"]).ToList();
fast = indicator_history_df["fast"]
slow = indicator_history_df["slow"]
signal = indicator_history_df["signal"]
histogram = indicator_history_df["histogram"]

# Alternative way
# fast = indicator_history_df.fast
# slow = indicator_history_df.slow
# signal = indicator_history_df.signal
# histogram = indicator_history_df.histogram

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