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from QuantConnect.Data.Market import TradeBar
from datetime import datetime
from datetime import timedelta
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
import decimal as d
import pandas as pd
class BollingerBreakoutAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2015, 1, 1)
self.SetEndDate(2019, 12, 10)
self.SetCash(10000)
self.MOMP = dict()
for ticker in ["XLK", "XLF", "XLI", "XLY", "XLB", "XLP", "XLV", "XLU", "XLE"]:
symbol = self.AddEquity(ticker, Resolution.Daily).Symbol
self.MOMP[symbol] = self.MOMP(symbol, 5, Resolution.Daily)
self.SetWarmUp(26, Resolution.Daily)
self.SetBenchmark("SPY")
self.Schedule.On(self.DateRules.Every(DayOfWeek.Wednesday), self.TimeRules.At(12, 0), self.EveryWedAtNoon)
def OnData(self, data):
if not all([self.MOMP.IsReady for symbol, MOMP in self.MOMP.items()]):
return
df = self.History(MOMP[symbol], 5, Resolution.Daily)
self.log("df")
,
My strategy here (may not be the best) but is to set holdings on the highest momentum scoring symbol in the list on a weekly basis and dropping the previous if it is different or does not exist. I assume I need a dataframe including each symbol and its indicator value to find the highest scorer. How do I set up the dataframe and get the highest scoring symbol. Any help would be appreciated.
Thanks
Rahul Chowdhury
Hey Rory,
I've implemented the strategy you described. To find the symbol with the highest MOMP value in your dictionary, I sorted the dictionary by MOMP value and retrieved the first element.
Here is the backtest.
Best
Rahul
Rory Forrest
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