Is there a Built-In Function For VWAP Upper and Lower Bands?

Hi Nathan,

Upper/Lower bands are not part of the VWAP definition, and so our VWAP indicator doesn't include this information.

Best,
Shile Wen

Nathan,

Would you mine sharing the formula you used to manually calculate the upper/lower bands? I am looking for the same thing.

Kevin Chaney   My implementation was a bit unique due to the different resolutions used for data and VWAP values. But I hope this helps. Basically, you need to record your VWAP values in a list, then calculate upper and lower band values from the standard deviation of that list. This gets the last 390 minutes of VWAP values which is essentially the last day's VWAP values (390 minutes in a trading day). I'd recommend setting the pre-market and post-market Resolution to true in the initialization function so that the VWAP values don't get out of wack if there is an overnight gap.

self.vwaplist = [] #Creating a list to record previous VWAP values to get std deviation from
seconds = int(str(self.Time.time())[6:8]) #My resolution was set to seconds and needed to record VWAP at each minute
if seconds == 0: #Add VWAP Value each minute to list
    self.vwaplist.insert(0, self.vwap.Current.Value)
if len(self.vwaplist) == 391: #Drop the last VWAP Value in the list if list is full
    self.vwaplist.pop()
if len(self.vwaplist) < 390: #Return if list isn't full
    return

vwaparray = np.asarray(self.vwaplist) #Change list to array so that we can calculate std deviation
upperband = self.vwap.Current.Value + 2 * vwaparray.std() #Calculate Upper Band
lowerband = self.vwap.Current.Value - 2 * vwaparray.std() #Calculate Lower Band

Thanks, Nathan! Turns out I'm using the same resolutions as you (seconds consolidated to minutes) so this will be very helpful.

Is that block of code going under initialize?  Nothing has to get put under OnData to be continually updated?