Supported Indicators
Williams Percent R
Introduction
Williams %R, or just %R, is the current closing price in relation to the high and low of the past N days (for a given N). The value of this indicator fluctuates between -100 and 0. The symbol is said to be oversold when the oscillator is below -80%, and overbought when the oscillator is above -20%.
To view the implementation of this indicator, see the LEAN GitHub repository.
Using WILR Indicator
To create an automatic indicator for WilliamsPercentR, call the WILRwilr helper method from the QCAlgorithm class. The WILRwilr method creates a WilliamsPercentR 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 WilliamsPercentRAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private WilliamsPercentR _wilr;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_wilr = WILR(_symbol, 20);
}
public override void OnData(Slice data)
{
if (_wilr.IsReady)
{
// The current value of _wilr is represented by itself (_wilr)
// or _wilr.Current.Value
Plot("WilliamsPercentR", "wilr", _wilr);
// Plot all properties of abands
Plot("WilliamsPercentR", "maximum", _wilr.Maximum);
Plot("WilliamsPercentR", "minimum", _wilr.Minimum);
}
}
} class WilliamsPercentRAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._wilr = self.wilr(self._symbol, 20)
def on_data(self, slice: Slice) -> None:
if self._wilr.is_ready:
# The current value of self._wilr is represented by self._wilr.current.value
self.plot("WilliamsPercentR", "wilr", self._wilr.current.value)
# Plot all attributes of self._wilr
self.plot("WilliamsPercentR", "maximum", self._wilr.maximum.current.value)
self.plot("WilliamsPercentR", "minimum", self._wilr.minimum.current.value)For more information about this method, see the QCAlgorithm classQCAlgorithm class.
You can manually create a WilliamsPercentR 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. The indicator will only be ready after you prime it with enough data.
public class WilliamsPercentRAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private WilliamsPercentR _williamspercentr;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_williamspercentr = new WilliamsPercentR(20);
}
public override void OnData(Slice data)
{
if (data.Bars.TryGetValue(_symbol, out var bar))
_williamspercentr.Update(bar);
if (_williamspercentr.IsReady)
{
// The current value of _williamspercentr is represented by itself (_williamspercentr)
// or _williamspercentr.Current.Value
Plot("WilliamsPercentR", "williamspercentr", _williamspercentr);
// Plot all properties of abands
Plot("WilliamsPercentR", "maximum", _williamspercentr.Maximum);
Plot("WilliamsPercentR", "minimum", _williamspercentr.Minimum);
}
}
} class WilliamsPercentRAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._williamspercentr = WilliamsPercentR(20)
def on_data(self, slice: Slice) -> None:
bar = slice.bars.get(self._symbol)
if bar:
self._williamspercentr.update(bar)
if self._williamspercentr.is_ready:
# The current value of self._williamspercentr is represented by self._williamspercentr.current.value
self.plot("WilliamsPercentR", "williamspercentr", self._williamspercentr.current.value)
# Plot all attributes of self._williamspercentr
self.plot("WilliamsPercentR", "maximum", self._williamspercentr.maximum.current.value)
self.plot("WilliamsPercentR", "minimum", self._williamspercentr.minimum.current.value)For more information about this indicator, see its referencereference.
Indicator History
To get the historical data of the WilliamsPercentR 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 WilliamsPercentRAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private WilliamsPercentR _wilr;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_wilr = WILR(_symbol, 20);
var indicatorHistory = IndicatorHistory(_wilr, _symbol, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(_wilr, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(_wilr, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
// Access all attributes of indicatorHistory
var maximum = indicatorHistory.Select(x => ((dynamic)x).Maximum).ToList();
var minimum = indicatorHistory.Select(x => ((dynamic)x).Minimum).ToList();
}
} class WilliamsPercentRAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._wilr = self.wilr(self._symbol, 20)
indicator_history = self.indicator_history(self._wilr, self._symbol, 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(self._wilr, self._symbol, timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(self._wilr, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
# Access all attributes of indicator_history
indicator_history_df = indicator_history.data_frame
maximum = indicator_history_df["maximum"]
minimum = indicator_history_df["minimum"]You can also see our Videos. You can also get in touch with us via Discord.
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