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Trying to colsolidate daily data in a monthly bar. Could I then calculate monthly performance of each Sector ETF from the monthly bar? Would there be an easy way to calculate the performance of each sector in the Rebalance function, after the IsWarmingUp method? Appreciate any ideas to get the code to "Build" and calculate the monthly sector perforemance. Thanks ....
Here's the code:
# Monthly ETF Rollover Strategy
# Use 11 Sector ETFs (XLB, XLC, XLE, XLF, XLI, XLK, XLP, XLRE, XLU, XLV, and XLY), equal weight the TOP3 ETF’s on 1st Day of the Month. Hold asset class Sector ETF’s for 1 month.
# If ETF is still in the TOP3 at month end, Keep It
import numpy as np
import pandas as pd
from datetime import datetime
class EmmausAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 5, 1)
self.SetEndDate(datetime.now())
self.SetCash(100000)
self.data = {}
period = 30
self.SetWarmUp(period)
# choose 11 sector ETFs
self.symbols = ["XLB", # Materials
"XLC", # Communication Services
"XLE", # Energy
"XLF", # Financials
"XLI", # Industrials
"XLK", # Technology
"XLP", # Staples
"XLRE", # Real Estate
"XLU", # Utilities
"XLV", # Health Care
"XLY"] # Discretionary
for symbol in self.symbols:
self.AddEquity(symbol, Resolution.Daily)
self.Consolidate(symbol, CalendarType.Monthly, self.OnDataConsolidated)
# shcedule the function to fire at the month start
self.Schedule.On(self.DateRules.MonthStart("XLB"), self.TimeRules.AfterMarketOpen("XLB", 10), self.Rebalance)
def OnData(self, data):
if self.IsWarmingUp: return
def OnDataConsolidated(self, bar):
self.currentBar = bar
def Rebalance(self):
if self.IsWarmingUp: return
top3 = pd.Series(self.data).sort_values(ascending = False)[:3]
for kvp in self.Portfolio:
security_hold = kvp.Value
# liquidate the security which is no longer in the top3 momentum list
if security_hold.Invested and (security_hold.Symbol.Value not in top3.index):
self.Liquidate(security_hold.Symbol)
for symbol in top3.index:
self.SetHoldings(symbol, 1/len(top3))
Alexandre Catarino
Hi Mike Reichard ,
The algorithm can create the RateOfChangePercent manually and register it to a monthly consolidator (see attached example).
Alternatively, since the algorithm is rebalancing monthly, it can simply make a historical request for all symbols and calculate the monthly return.
Mike Reichard
Mike Reichard
func = lambda x:x[1].Current.Value
Top3 = {x[0]:x[1].Current.Value
for x in sorted(self.data.items(), key=func, reverse=True)[:3]}
Is Top3 just a python/panda series with the symbols of the lowest performing sector ETF’s? How do I learn more about the “lambda” function/method or whatever that is?
Really appreciate your help. Thank you!
Alexandre Catarino
Hi Mike Reichard ,
I used the built-in sorted function to sort the dictionary of returns keyed by Symbol object because it is more efficient than using pandas. For details, please check out the Python How To: Sorting HOW TO
Mike Reichard
Mike Reichard
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