| Overall Statistics |
|
Total Trades 5 Average Win 0% Average Loss -0.41% Compounding Annual Return -13.354% Drawdown 2.600% Expectancy -1 Net Profit -1.867% Sharpe Ratio -2.272 Probabilistic Sharpe Ratio 7.355% Loss Rate 100% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.004 Beta 0.246 Annual Standard Deviation 0.042 Annual Variance 0.002 Information Ratio 2.198 Tracking Error 0.126 Treynor Ratio -0.388 Total Fees $5.00 Estimated Strategy Capacity $160000000.00 Lowest Capacity Asset GSG TKH7EPK7SRC5 |
# https://quantpedia.com/Screener/Details/2
# Use 5 ETFs (SPY - US stocks, EFA - foreign stocks, BND - bonds, VNQ - REITs, GSG - commodities).
# Pick 3 ETFs with strongest 12 month momentum into your portfolio and weight them equally.
# Hold for 1 month and then rebalance.
import pandas as pd
from datetime import datetime
class AssetClassMomentumAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2022, 1, 1)
self.SetEndDate(datetime.now())
self.SetCash(10000)
# create a dictionary to store momentum indicators for all symbols
self.data = {}
period = 5*21
self.symbols = ["SPY", "EFA", "BND", "VNQ", "GSG", "XLE", "ARKK", "EEM", "DBP"]
# warm up the MOM indicator
self.SetWarmUp(period)
for symbol in self.symbols:
self.AddEquity(symbol, Resolution.Daily)
self.data[symbol] = self.MOM(symbol, period, Resolution.Daily)
# shcedule the function to fire at the month start
self.Schedule.On(self.DateRules.MonthStart("SPY"), self.TimeRules.AfterMarketOpen("SPY"), self.Rebalance)
self.Settings.FreePortfolioValuePercentage=0.2
def OnData(self, data):
stock = self.symbols[0]
close = data[stock].Close
#self.Debug("{} Symbol:{} Close:{:.2f}".format(self.Time, stock, close))
self.value=close
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)
added_symbols = []
for symbol in top3.index:
if not self.Portfolio[symbol].Invested:
added_symbols.append(symbol)
for added in added_symbols:
lastPrice = self.value
sharesToBuy= self.Portfolio.MarginRemaining*(1-self.Settings.FreePortfolioValuePercentage) // len(added_symbols) // lastPrice
self.Debug("{} Shares to buy Symbol:{} Close:{} RemMargin:{:.2f} sharesToBuy:{}"
.format(self.Time, added, lastPrice , self.Portfolio.MarginRemaining, sharesToBuy))
self.MarketOrder(added, sharesToBuy)