Supported Indicators
Stochastic
Introduction
This indicator computes the Slow Stochastics %K and %D. The Fast Stochastics %K is is computed by (Current Close Price - Lowest Price of given Period) / (Highest Price of given Period - Lowest Price of given Period) multiplied by 100. Once the Fast Stochastics %K is calculated the Slow Stochastic %K is calculated by the average/smoothed price of of the Fast %K with the given period. The Slow Stochastics %D is then derived from the Slow Stochastics %K with the given period.
Using STO Indicator
To create an automatic indicators for Stochastic, call the STO helper method from the QCAlgorithm class. The STO method creates a Stochastic 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 StochasticAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private Stochastic _sto;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_sto = STO("SPY", 20, 10, 20);
}
public override void OnData(Slice data)
{
if (_sto.IsReady)
{
Plot("Stochastic", "sto", _sto);
Plot("Stochastic", "faststoch", _sto.FastStoch);
Plot("Stochastic", "stochk", _sto.StochK);
Plot("Stochastic", "stochd", _sto.StochD);
}
}
} class StochasticAlgorithm(QCAlgorithm):
def Initialize(self) -> None:
self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
self.sto = self.STO("SPY", 20, 10, 20)
def OnData(self, slice: Slice) -> None:
if self.sto.IsReady:
self.Plot("Stochastic", "sto", self.sto.Current.Value)
self.Plot("Stochastic", "faststoch", self.sto.FastStoch.Current.Value)
self.Plot("Stochastic", "stochk", self.sto.StochK.Current.Value)
self.Plot("Stochastic", "stochd", self.sto.StochD.Current.Value)
The following reference table describes the STO method:
STO()1/2
Stochastic QuantConnect.Algorithm.QCAlgorithm.STO (
Symbol symbol,
Int32 period,
Int32 kPeriod,
Int32 dPeriod,
*Nullable<Resolution> resolution,
*Func<IBaseData, TradeBar> selector
)
Creates a new Stochastic indicator.
STO()2/2
Stochastic QuantConnect.Algorithm.QCAlgorithm.STO (
Symbol symbol,
Int32 period,
*Nullable<Resolution> resolution,
*Func<IBaseData, TradeBar> selector
)
Overload short hand to create a new Stochastic indicator; defaulting to the 3 period for dStoch.
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 Stochastic 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 StochasticAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private Stochastic _sto;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_sto = new Stochastic(20, 10, 20);
}
public override void OnData(Slice data)
{
if (data.Bars.TryGeValue(_symbol, out var bar))
{
_sto.Update(bar);
}
if (_sto.IsReady)
{
Plot("Stochastic", "sto", _sto);
Plot("Stochastic", "faststoch", _sto.FastStoch);
Plot("Stochastic", "stochk", _sto.StochK);
Plot("Stochastic", "stochd", _sto.StochD);
}
}
} class StochasticAlgorithm(QCAlgorithm):
def Initialize(self) -> None:
self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
self.sto = Stochastic(20, 10, 20)
def OnData(self, slice: Slice) -> None:
bar = data.Bars.get(self.symbol)
if bar:
self.sto.Update(bar)
if self.sto.IsReady:
self.Plot("Stochastic", "sto", self.sto.Current.Value)
self.Plot("Stochastic", "faststoch", self.sto.FastStoch.Current.Value)
self.Plot("Stochastic", "stochk", self.sto.StochK.Current.Value)
self.Plot("Stochastic", "stochd", self.sto.StochD.Current.Value)
To register a manual indicator for automatic updates with the security data, call the RegisterIndicator method.
public class StochasticAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private Stochastic _sto;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_sto = new Stochastic(20, 10, 20);
RegisterIndicator(_symbol, _sto, Resolution.Daily);
}
public override void OnData(Slice data)
{
if (_sto.IsReady)
{
Plot("Stochastic", "sto", _sto);
Plot("Stochastic", "faststoch", _sto.FastStoch);
Plot("Stochastic", "stochk", _sto.StochK);
Plot("Stochastic", "stochd", _sto.StochD);
}
}
} class StochasticAlgorithm(QCAlgorithm):
def Initialize(self) -> None:
self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
self.sto = Stochastic(20, 10, 20)
self.RegisterIndicator(self.symbol, self.sto, Resolution.Daily)
def OnData(self, slice: Slice) -> None:
if self.sto.IsReady:
self.Plot("Stochastic", "sto", self.sto.Current.Value)
self.Plot("Stochastic", "faststoch", self.sto.FastStoch.Current.Value)
self.Plot("Stochastic", "stochk", self.sto.StochK.Current.Value)
self.Plot("Stochastic", "stochd", self.sto.StochD.Current.Value)
The following reference table describes the Stochastic constructor:
Stochastic()1/2
Stochastic QuantConnect.Indicators.Stochastic (
string name,
int period,
int kPeriod,
int dPeriod
)
Creates a new Stochastics Indicator from the specified periods.
Stochastic()2/2
Stochastic QuantConnect.Indicators.Stochastic (
int period,
int kPeriod,
int dPeriod
)
Creates a new Stochasti indicator from the specified inputs.
Visualization
The following image shows plot values of selected properties of Stochastic using the plotly library.
You can also see our Videos. You can also get in touch with us via Discord.
Did you find this page helpful?
