Supported Indicators
Target Downside Deviation
Introduction
This indicator computes the n-period target downside deviation. The target downside deviation is defined as the root-mean-square, or RMS, of the deviations of the realized return’s underperformance from the target return where all returns above the target return are treated as underperformance of 0. Reference: https://www.cmegroup.com/education/files/rr-sortino-a-sharper-ratio.pdf
To view the implementation of this indicator, see the LEAN GitHub repository.
Using TDD Indicator
To create an automatic indicators for TargetDownsideDeviation, call the TDD helper method from the QCAlgorithm class. The TDD method creates a TargetDownsideDeviation 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 TargetDownsideDeviationAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private TargetDownsideDeviation _tdd;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_tdd = TDD(_symbol, 50);
}
public override void OnData(Slice data)
{
if (_tdd.IsReady)
{
// The current value of _tdd is represented by itself (_tdd)
// or _tdd.Current.Value
Plot("TargetDownsideDeviation", "tdd", _tdd);
}
}
} class TargetDownsideDeviationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._tdd = self.tdd(self._symbol, 50)
def on_data(self, slice: Slice) -> None:
if self._tdd.is_ready:
# The current value of self._tdd is represented by self._tdd.current.value
self.plot("TargetDownsideDeviation", "tdd", self._tdd.current.value)
The following reference table describes the TDD method:
tdd(symbol, period, minimum_acceptable_return=0.0, resolution=None, selector=None)[source]Creates a new TargetDownsideDeviation indicator. The target downside deviation is defined as the root-mean-square, or RMS, of the deviations of the realized return’s underperformance from the target return where all returns above the target return are treated as underperformance of 0.
- symbol (Symbol) — The symbol whose TDD we want
- period (int) — The period over which to compute the TDD
- minimum_acceptable_return (float, optional) — The resolution
- resolution (Resolution, optional) — Minimum acceptable return (MAR) for the target downside deviation calculation
- selector (Callable[IBaseData, float], optional) — x.Value)
The TargetDownsideDeviation indicator for the requested symbol over the specified period
TDD(symbol, period, minimumAcceptableReturn=0.0, resolution=None, selector=None)[source]Creates a new TargetDownsideDeviation indicator. The target downside deviation is defined as the root-mean-square, or RMS, of the deviations of the realized return’s underperformance from the target return where all returns above the target return are treated as underperformance of 0.
- symbol (Symbol) — The symbol whose TDD we want
- period (Int32) — The period over which to compute the TDD
- minimumAcceptableReturn (Double, optional) — The resolution
- resolution (Resolution, optional) — Minimum acceptable return (MAR) for the target downside deviation calculation
- selector (Func<IBaseData, Decimal>, optional) — x.Value)
The TargetDownsideDeviation indicator for the requested symbol over the specified period
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 TargetDownsideDeviation 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 TargetDownsideDeviationAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private TargetDownsideDeviation _tdd;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_tdd = new TargetDownsideDeviation(TargetDownsideDeviation(50), RateOfChange(1));
}
public override void OnData(Slice data)
{
if (data.Bars.TryGetValue(_symbol, out var bar))
{
_tdd.Update(bar.EndTime, bar.Close);
}
if (_tdd.IsReady)
{
// The current value of _tdd is represented by itself (_tdd)
// or _tdd.Current.Value
Plot("TargetDownsideDeviation", "tdd", _tdd);
}
}
} class TargetDownsideDeviationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._tdd = TargetDownsideDeviation(TargetDownsideDeviation(50), RateOfChange(1))
def on_data(self, slice: Slice) -> None:
bar = slice.bars.get(self._symbol)
if bar:
self._tdd.update(bar.EndTime, bar.Close)
if self._tdd.is_ready:
# The current value of self._tdd is represented by self._tdd.current.value
self.plot("TargetDownsideDeviation", "tdd", self._tdd.current.value)
To register a manual indicator for automatic updates with the security data, call the RegisterIndicatorregister_indicator method.
public class TargetDownsideDeviationAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private TargetDownsideDeviation _tdd;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_tdd = new TargetDownsideDeviation(TargetDownsideDeviation(50), RateOfChange(1));
RegisterIndicator(_symbol, _tdd, Resolution.Daily);
}
public override void OnData(Slice data)
{
if (_tdd.IsReady)
{
// The current value of _tdd is represented by itself (_tdd)
// or _tdd.Current.Value
Plot("TargetDownsideDeviation", "tdd", _tdd);
}
}
} class TargetDownsideDeviationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._tdd = TargetDownsideDeviation(TargetDownsideDeviation(50), RateOfChange(1))
self.register_indicator(self._symbol, self._tdd, Resolution.DAILY)
def on_data(self, slice: Slice) -> None:
if self._tdd.is_ready:
# The current value of self._tdd is represented by self._tdd.current.value
self.plot("TargetDownsideDeviation", "tdd", self._tdd.current.value)
The following reference table describes the TargetDownsideDeviation constructor:
TargetDownsideDeviation
This indicator computes the n-period target downside deviation. The target downside deviation is defined as the root-mean-square, or RMS, of the deviations of the realized return’s underperformance from the target return where all returns above the target return are treated as underperformance of 0. Reference: https://www.cmegroup.com/education/files/rr-sortino-a-sharper-ratio.pdf
get_enumerator()Returns an enumerator that iterates through the history window.
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}
str
update(time, value)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- time (datetime)
- value (float)
bool
update(input)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- input (IBaseData)
bool
consolidatorsThe data consolidators associated with this indicator if any
The data consolidators associated with this indicator if any
ISet[IDataConsolidator]
currentGets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
is_readyGets a flag indicating when this indicator is ready and fully initialized
Gets a flag indicating when this indicator is ready and fully initialized
bool
itemIndexes 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.
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.
IndicatorDataPoint
nameGets a name for this indicator
Gets a name for this indicator
str
periodGets the period of this window indicator
Gets the period of this window indicator
int
previousGets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
samplesGets the number of samples processed by this indicator
Gets the number of samples processed by this indicator
int
warm_up_periodRequired period, in data points, to the indicator to be ready and fully initialized
Required period, in data points, to the indicator to be ready and fully initialized
int
windowA rolling window keeping a history of the indicator values of a given period
A rolling window keeping a history of the indicator values of a given period
RollingWindow[IndicatorDataPoint]
TargetDownsideDeviation
This indicator computes the n-period target downside deviation. The target downside deviation is defined as the root-mean-square, or RMS, of the deviations of the realized return’s underperformance from the target return where all returns above the target return are treated as underperformance of 0. Reference: https://www.cmegroup.com/education/files/rr-sortino-a-sharper-ratio.pdf
GetEnumerator()Returns an enumerator that iterates through the history window.
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}
String
Update(time, value)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- time (DateTime)
- value (decimal)
Boolean
Update(input)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- input (IBaseData)
Boolean
ConsolidatorsThe data consolidators associated with this indicator if any
The data consolidators associated with this indicator if any
ISet<IDataConsolidator>
CurrentGets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
IsReadyGets a flag indicating when this indicator is ready and fully initialized
Gets a flag indicating when this indicator is ready and fully initialized
bool
NameGets a name for this indicator
Gets a name for this indicator
string
PeriodGets the period of this window indicator
Gets the period of this window indicator
Int32
PreviousGets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
SamplesGets the number of samples processed by this indicator
Gets the number of samples processed by this indicator
int
WarmUpPeriodRequired period, in data points, to the indicator to be ready and fully initialized
Required period, in data points, to the indicator to be ready and fully initialized
Int32
WindowA rolling window keeping a history of the indicator values of a given period
A rolling window keeping a history of the indicator values of a given period
RollingWindow<IndicatorDataPoint>
[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.
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.
IndicatorDataPoint
Visualization
The following image shows plot values of selected properties of TargetDownsideDeviation using the plotly library.
Indicator History
To get the historical data of the TargetDownsideDeviation 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 TargetDownsideDeviationAlgorithm : QCAlgorithm
{
private Symbol _symbol;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
var tdd = TDD(_symbol, 50);
var countIndicatorHistory = IndicatorHistory(tdd, _symbol, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(tdd, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(tdd, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
}
} class TargetDownsideDeviationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
tdd = self.tdd(self._symbol, 50)
count_indicator_history = self.indicator_history(tdd, self._symbol, 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(tdd, self._symbol, timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(tdd, 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(tdd, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(tdd, 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(tdd, history);
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