Supported Indicators

Commodity Channel Index

Introduction

This indicator represents the traditional commodity channel index (CCI) CCI = (Typical Price - 20-period SMA of TP) / (.015 * Mean Deviation) Typical Price (TP) = (High + Low + Close)/3 Constant = 0.015 There are four steps to calculating the Mean Deviation, first, subtract the most recent 20-period average of the typical price from each period's typical price. Second, take the absolute values of these numbers. Third, sum the absolute values. Fourth, divide by the total number of periods (20).

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

Using CCI Indicator

To create an automatic indicators for CommodityChannelIndex, call the CCI helper method from the QCAlgorithm class. The CCI method creates a CommodityChannelIndex 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 CommodityChannelIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private CommodityChannelIndex _cci;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _cci = CCI(_symbol, 20, MovingAverageType.Simple);
    }

    public override void OnData(Slice data)
    {
        if (_cci.IsReady)
        {
            // The current value of _cci is represented by itself (_cci)
            // or _cci.Current.Value
            Plot("CommodityChannelIndex", "cci", _cci);
            // Plot all properties of cci
            Plot("CommodityChannelIndex", "typicalpriceaverage", _cci.TypicalPriceAverage);
            Plot("CommodityChannelIndex", "typicalpricemeandeviation", _cci.TypicalPriceMeanDeviation);
        }
    }
}
class CommodityChannelIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._cci = self.cci(self._symbol, 20, MovingAverageType.Simple)

    def on_data(self, slice: Slice) -> None:
        if self._cci.is_ready:
            # The current value of self._cci is represented by self._cci.current.value
            self.plot("CommodityChannelIndex", "cci", self._cci.current.value)
            # Plot all attributes of self._cci
            self.plot("CommodityChannelIndex", "typical_price_average", self._cci.typical_price_average.current.value)
            self.plot("CommodityChannelIndex", "typical_price_mean_deviation", self._cci.typical_price_mean_deviation.current.value)

The following reference table describes the CCI method:

cci(symbol, period, moving_average_type=0, resolution=None, selector=None)[source]

Creates a new CommodityChannelIndex indicator. The indicator will be automatically updated on the given resolution.

Parameters:
  • symbol (Symbol) — The symbol whose CCI we want
  • period (int) — The period over which to compute the CCI
  • moving_average_type (MovingAverageType, optional) — The type of moving average to use in computing the typical price average
  • 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:

The CommodityChannelIndex indicator for the requested symbol over the specified period

Return type:

CommodityChannelIndex

CCI(symbol, period, movingAverageType=0, resolution=None, selector=None)[source]

Creates a new CommodityChannelIndex indicator. The indicator will be automatically updated on the given resolution.

Parameters:
  • symbol (Symbol) — The symbol whose CCI we want
  • period (Int32) — The period over which to compute the CCI
  • movingAverageType (MovingAverageType, optional) — The type of moving average to use in computing the typical price average
  • 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:

The CommodityChannelIndex indicator for the requested symbol over the specified period

Return type:

CommodityChannelIndex

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.

The following table describes the MovingAverageType enumeration members:

To avoid parameter ambiguity, use the resolution argument to set the Resolution.

public class CommodityChannelIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private CommodityChannelIndex _cci;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Hour).Symbol;
        _cci = CCI(_symbol, 20, MovingAverageType.Simple, resolution: Resolution.Daily);
    }
}
class CommodityChannelIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.HOUR).Symbol
        self._cci = self.cci(self._symbol, 20, MovingAverageType.Simple, resolution=Resolution.DAILY)

You can manually create a CommodityChannelIndex 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 CommodityChannelIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private CommodityChannelIndex _cci;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _cci = new CommodityChannelIndex(20, MovingAverageType.Simple);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _cci.Update(bar);
        }
   
        if (_cci.IsReady)
        {
            // The current value of _cci is represented by itself (_cci)
            // or _cci.Current.Value
            Plot("CommodityChannelIndex", "cci", _cci);
            // Plot all properties of cci
            Plot("CommodityChannelIndex", "typicalpriceaverage", _cci.TypicalPriceAverage);
            Plot("CommodityChannelIndex", "typicalpricemeandeviation", _cci.TypicalPriceMeanDeviation);
        }
    }
}
class CommodityChannelIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._cci = CommodityChannelIndex(20, MovingAverageType.Simple)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._cci.update(bar)
        if self._cci.is_ready:
            # The current value of self._cci is represented by self._cci.current.value
            self.plot("CommodityChannelIndex", "cci", self._cci.current.value)
            # Plot all attributes of self._cci
            self.plot("CommodityChannelIndex", "typical_price_average", self._cci.typical_price_average.current.value)
            self.plot("CommodityChannelIndex", "typical_price_mean_deviation", self._cci.typical_price_mean_deviation.current.value)

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

public class CommodityChannelIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private CommodityChannelIndex _cci;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _cci = new CommodityChannelIndex(20, MovingAverageType.Simple);
        RegisterIndicator(_symbol, _cci, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_cci.IsReady)
        {
            // The current value of _cci is represented by itself (_cci)
            // or _cci.Current.Value
            Plot("CommodityChannelIndex", "cci", _cci);
            // Plot all properties of cci
            Plot("CommodityChannelIndex", "typicalpriceaverage", _cci.TypicalPriceAverage);
            Plot("CommodityChannelIndex", "typicalpricemeandeviation", _cci.TypicalPriceMeanDeviation);
        }
    }
}
class CommodityChannelIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._cci = CommodityChannelIndex(20, MovingAverageType.Simple)
        self.register_indicator(self._symbol, self._cci, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self._cci.is_ready:
            # The current value of self._cci is represented by self._cci.current.value
            self.plot("CommodityChannelIndex", "cci", self._cci.current.value)
            # Plot all attributes of self._cci
            self.plot("CommodityChannelIndex", "typical_price_average", self._cci.typical_price_average.current.value)
            self.plot("CommodityChannelIndex", "typical_price_mean_deviation", self._cci.typical_price_mean_deviation.current.value)

The following reference table describes the CommodityChannelIndex constructor:

CommodityChannelIndex

class QuantConnect.Indicators.CommodityChannelIndex[source]

Represents the traditional commodity channel index (CCI) CCI = (Typical Price - 20-period SMA of TP) / (.015 * Mean Deviation) Typical Price (TP) = (High + Low + Close)/3 Constant = 0.015 There are four steps to calculating the Mean Deviation, first, subtract the most recent 20-period average of the typical price from each period's typical price. Second, take the absolute values of these numbers. Third, sum the absolute values. Fourth, divide by the total number of periods (20).

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 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 moving_average_type

Gets the type of moving average

Returns:

Gets the type of moving average

Return type:

MovingAverageType

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 typical_price_average

Keep track of the simple moving average of the typical price

Returns:

Keep track of the simple moving average of the typical price

Return type:

IndicatorBase[IndicatorDataPoint]

property typical_price_mean_deviation

Keep track of the mean absolute deviation of the typical price

Returns:

Keep track of the mean absolute deviation of the typical price

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]

CommodityChannelIndex

class QuantConnect.Indicators.CommodityChannelIndex[source]

Represents the traditional commodity channel index (CCI) CCI = (Typical Price - 20-period SMA of TP) / (.015 * Mean Deviation) Typical Price (TP) = (High + Low + Close)/3 Constant = 0.015 There are four steps to calculating the Mean Deviation, first, subtract the most recent 20-period average of the typical price from each period's typical price. Second, take the absolute values of these numbers. Third, sum the absolute values. Fourth, divide by the total number of periods (20).

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 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 MovingAverageType

Gets the type of moving average

Returns:

Gets the type of moving average

Return type:

MovingAverageType

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 TypicalPriceAverage

Keep track of the simple moving average of the typical price

Returns:

Keep track of the simple moving average of the typical price

Return type:

IndicatorBase<IndicatorDataPoint>

property TypicalPriceMeanDeviation

Keep track of the mean absolute deviation of the typical price

Returns:

Keep track of the mean absolute deviation of the typical price

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 CommodityChannelIndex using the plotly library.

CommodityChannelIndex line plot.

Indicator History

To get the historical data of the CommodityChannelIndex 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 CommodityChannelIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        var cci = CCI(_symbol, 20, MovingAverageType.Simple);
        var countIndicatorHistory = IndicatorHistory(cci, _symbol, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(cci, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(cci, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
    }
}
class CommodityChannelIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        cci = self.cci(self._symbol, 20, MovingAverageType.Simple)
        count_indicator_history = self.indicator_history(cci, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(cci, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(cci, 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(cci, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(cci, 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(cci, history);

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

var typicalpriceaverage = indicatorHistory.Select(x => ((dynamic)x).TypicalPriceAverage).ToList();
var typicalpricemeandeviation = indicatorHistory.Select(x => ((dynamic)x).TypicalPriceMeanDeviation).ToList();

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

typical_price_average = indicator_history_df["typical_price_average"]
typical_price_mean_deviation = indicator_history_df["typical_price_mean_deviation"]

# Alternative way
# typical_price_average = indicator_history_df.typical_price_average
# typical_price_mean_deviation = indicator_history_df.typical_price_mean_deviation

You can also see our Videos. You can also get in touch with us via Discord.

Did you find this page helpful?

Contribute to the documentation: