Indicators
Trade Bar Indicators
Create Subscriptions
You need to subscribe to some market data in order to calculate indicator values.
var qb = new QuantBook(); var symbol = qb.AddEquity("SPY").Symbol;
qb = QuantBook() symbol = qb.AddEquity("SPY").Symbol
Create Indicator Timeseries
You need to subscribe to some market data and create an indicator in order to calculate a timeseries of indicator values. In this example, use a 20-period VolumeWeightedAveragePriceIndicator
indicator.
var vwap = new VolumeWeightedAveragePriceIndicator(20);
vwap = VolumeWeightedAveragePriceIndicator(20)
You can create the indicator timeseries with the Indicator
helper method or you can manually create the timeseries.
Indicator Helper Method
To create an indicator timeseries with the helper method, call the Indicator
method.
var vwapIndicator = qb.Indicator(vwap, symbol, 50, Resolution.Daily);
vwap_dataframe = qb.Indicator(vwap, symbol, 50, Resolution.Daily)

Manually Create the Indicator Timeseries
Follow these steps to create an indicator timeseries:
- Get some historical data.
- Create a
RollingWindow
for each attribute of the indicator to hold their values. - Attach a handler method to the indicator that updates the
RollingWindow
objects. - Iterate through the historical market data and update the indicator.
- Display the data.
- Populate a
DataFrame
with the data in theRollingWindow
objects.
var history = qb.History(symbol, 70, Resolution.Daily);
history = qb.History[TradeBar](symbol, 70, Resolution.Daily)
var time = new RollingWindow<DateTime>(50); var window = new Dictionary<string, RollingWindow<decimal>>(); window["volumeweightedaveragepriceindicator"] = new RollingWindow<decimal>(50);
window = {} window['time'] = RollingWindow[DateTime](50) window['volumeweightedaveragepriceindicator'] = RollingWindow[float](50)
vwap.Updated += (sender, updated) => { time.Add(updated.EndTime); window["volumeweightedaveragepriceindicator"].Add(updated); };
def UpdateVWAPWindow(sender: object, updated: IndicatorDataPoint) -> None: window['time'].Add(updated.EndTime) window["volumeweightedaveragepriceindicator"].Add(updated.Value) vwap.Updated += UpdateVWAPWindow
When the indicator receives new data, the preceding handler method adds the new IndicatorDataPoint
values into the respective RollingWindow
.
foreach(var bar in history){ // Update the indicators with the whole TradeBar. vwap.Update(bar); }
for bar in history: vwap.Update(bar)
Console.WriteLine($"time,{string.Join(',', window.Select(kvp => kvp.Key))}"); foreach (var i in Enumerable.Range(0, 5).Reverse()) { var data = string.Join(", ", window.Select(kvp => Math.Round(kvp.Value[i],6))); Console.WriteLine($"{time[i]:yyyyMMdd}, {data}"); }

vwap_dataframe = pd.DataFrame(window).set_index('time')

Plot Indicators
Jupyter Notebooks don't currently support libraries to plot historical data, but we are working on adding the functionality. Until the functionality is added, use Python to plot TradeBar indicators.
Follow these steps to plot the indicator values:
- Call the
plot
method. - Show the plots.
vwap_indicator.plot(title="SPY VWAP(20)", figsize=(15, 10))
plt.show()
