Rolling window of consolidated indicator data

# Imports
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Common")
AddReference("QuantConnect.Jupyter")
AddReference("QuantConnect.Indicators")
AddReference("QuantConnect.Algorithm")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data import *
from QuantConnect.Data.Custom import *
from QuantConnect.Data.Market import TradeBar, QuoteBar
from QuantConnect.Data.Consolidators import *
from QuantConnect.Jupyter import *
from QuantConnect.Indicators import *
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np


class BasicTemplateAlgorithm(QCAlgorithm):

def Initialize(self):

self.symbol = "USDZAR"
self.highprice = None
self.lowprice = None
self.tidetrend = None
self.wavetrend = None

self.closeWindow = RollingWindow[float](4)

self.SetStartDate(2018,9,1) #Set Start Date
self.SetEndDate(datetime.now()) #Set End Date to Now
self.SetCash(1122) #Set Strategy Cash

self.AddForex(self.symbol, Resolution.Minute).SetLeverage(50.0)

# Create the rolling windows
# Creates MACDOH indicator and add to a rolling window when it is updated
self.MACD(self.symbol, 12, 26, 9, MovingAverageType.Exponential).Updated += self.MACDOHUpdated
self.macdoh = RollingWindow[float](5)

# Creates MACDTM indicator and add to a rolling window when it is updated
self.MACD(self.symbol, 12, 26, 9, MovingAverageType.Exponential).Updated += self.MACDTMUpdated
self.macdtm = RollingWindow[float](5)

# Creates BB indicator and add to a rolling window when it is updated
self.BB(self.symbol, 20, 1, MovingAverageType.Exponential, Resolution.Minute).Updated += self.BBUpdated
self.bb = RollingWindow[float](5)

# Creates RSI indicator and add to a rolling window when it is updated
self.RSI(self.symbol, 14, MovingAverageType.Simple, Resolution.Minute).Updated += self.RSIUpdated
self.rsi = RollingWindow[float](5)

oneHourConsolidator = QuoteBarConsolidator(timedelta(minutes=60))
oneHourConsolidator.DataConsolidated += self.OneHourBarHandler
self.RegisterIndicator(self.symbol, self.macdoh, oneHourConsolidator)
self.SubscriptionManager.AddConsolidator(self.symbol, oneHourConsolidator)

tenMinuteConsolidator = QuoteBarConsolidator(timedelta(minutes=10))
tenMinuteConsolidator.DataConsolidated += self.TenMinuteBarHandler
self.RegisterIndicator(self.symbol, self.macdtm, tenMinuteConsolidator)
self.RegisterIndicator(self.symbol, self.bb, tenMinuteConsolidator)
self.RegisterIndicator(self.symbol, self.rsi, tenMinuteConsolidator)
self.SubscriptionManager.AddConsolidator(self.symbol, tenMinuteConsolidator)

twoMinuteConsolidator = QuoteBarConsolidator(timedelta(minutes=2))
twoMinuteConsolidator.DataConsolidated += self.TwoMinuteBarHandler
self.SubscriptionManager.AddConsolidator(self.symbol, twoMinuteConsolidator)

self.SetWarmUp(120, Resolution.Minute)

#Pass (cause this is only for minute data)
def OnData(self, data):
pass

# Adds updated values to MACDOH rolling window
def MACDOHUpdated(self, sender, updated):
self.macdoh.Add(updated)

# Adds updated values to MACDTM rolling window
def MACDTMUpdated(self, sender, updated):
self.macdtm.Add(updated)

# Adds updated values to BB rolling window
def BBUpdated(self, sender, updated):
self.bb.Add(updated)

# Adds updated values to RSI rolling window
def RSIUpdated(self, sender, updated):
self.rsi.Add(updated)

def OneHourBarHandler(self, sender, consolidated):

if not (self.macdoh.IsReady): return

macd_hist_0 = self.macdoh[0].Current.Value - self.macdoh[0].Signal.Current.Value
macd_hist_1 = self.macdoh[1].Current.Value - self.macdoh[1].Signal.Current.Value
macd_hist_2 = self.macdoh[2].Current.Value - self.macdoh[2].Signal.Current.Value
macd_hist_3 = self.macdoh[3].Current.Value - self.macdoh[3].Signal.Current.Value


def TenMinuteBarHandler(self, sender, consolidated):

self.closeWindow.Add(data[self.symbol].Close)

if not (self.closeWindow.IsReady and self.macdoh.IsReady and self.macdtm.IsReady and self.bb.IsReady and self.rsi.IsReady): return

price_0 = self.closeWindow[0]
price_1 = self.closeWindow[1]
price_2 = self.closeWindow[2]

self.highprice = max(price_0, price_1, price_2)
self.lowprice = min(price_0, price_1, price_2)

currrsi = self.rsi[0].Current.Value
currbbub = self.bb[0].UpperBand.Current.Value
currbblb = self.bb[0].LowerBand.Current.Value

macd_hist_0 = self.macdtm[0].Current.Value - self.macdtm[0].Signal.Current.Value
macd_hist_1 = self.macdtm[1].Current.Value - self.macdtm[1].Signal.Current.Value
macd_hist_2 = self.macdtm[2].Current.Value - self.macdtm[2].Signal.Current.Value
macd_hist_3 = self.macdtm[3].Current.Value - self.macdtm[3].Signal.Current.Value

Thank you for attaching the source code! The reason for the error is because self.RegisterIndicator requires the parameters self.RegisterIndicator(symbol, indicator, consolidator). However, the code above gave a RollingWindow instead of an indicator. After changing the types, the error did not come up again. However, there were a few other errors. Here is a reference to the documentation.

One of the errors was in the method TenMinuteBarHandle. data is not defined in the line: 

I went ahead and changed that to Self.Securities[self.symbol].Close. Another error was the types contained in the RollingWindow. I changed that to IndicatorDataPoint so that IndicatorDataPoint.Value could be called on the data. Below is the algorithm in progress:

@Gurumeher THANK YOU SO MUCH!!!! I truly appreciate your help with this. Everything is now working except for lines 119 to 126. Eveytime Itry backtest, I get the following error: "'IndicatorDataPoint' object has no attribute 'Current'" Its seems like I can only access the (.Value) data from the rolling windows. Hence, I cant access the Current, UpperBand, LowerBand or Signal data from the bollinger band or MACD. Is there a way access this information? 

A potential solution to this can be to change the type of the RollingWindows in Initialize() from IndicatorDataPoint to the object of the indicator itself, i.e. MovingAverageConvergenceDivergence, BollingerBands and RelativeStrengthIndex. 

This way, when accessing the objects from the RollingWindow, you have the ability to call any one of the objects' properties.

I tried this code but it throws a type error. When using IndicatorDataPoints, it throws an attribute error, saying it has no attribute “current”, and when using the object of the indicator itself, it throws a type error. 

Hi Xavier Lopez,
In the above algorithm when initializing the RollingWindows' we need to assign the type as IndicatorDataPoint instead of the indicator name. Also, we do not need to use the Current attribute when accessing an IndicatorDatapoint just use the Value attribute. IndicatorDataPoints only store one piece of information. To get the upper/lower band information, we need to create separate RollingWindows that are updated using the upper and lower band's information. Refer to the following thread for more information and an example.
Best,
Varad Kabade

Thank you this has been help full for me to.