| Overall Statistics |
|
Total Trades 63 Average Win 5.97% Average Loss -2.22% Compounding Annual Return 62.514% Drawdown 35.800% Expectancy 1.182 Net Profit 70.941% Sharpe Ratio 1.179 Probabilistic Sharpe Ratio 58.321% Loss Rate 41% Win Rate 59% Profit-Loss Ratio 2.68 Alpha 0.438 Beta 0.182 Annual Standard Deviation 0.407 Annual Variance 0.166 Information Ratio 0.598 Tracking Error 0.417 Treynor Ratio 2.632 Total Fees $579.04 |
# Speculation Rollover Strategy
# Use 12 Speculative ETFs (DWT, UWT, DGAZ, UGAZ, TZA, TNA, ERY, ERX, FAZ, FAS, TLT, and TBT), 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 TOPX 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, 1, 1)
self.SetEndDate(datetime.now())
self.SetCash(100000)
# choose 13 speculative ETF
tickers = [ "SPY", # S&P500 ETF
"DWT", # Triple Oil Down
"UWT", # Triple Oil Up
"DGAZ", # Triple Natural Gas Down
"UGAZ", # Triple Natural Gas Up
"TZA", # Triple Small Cap Down
"TNA", # Triple Small Cap Up
"ERY", # Triple Energy Down
"ERX", # Triple Energy Up
"FAZ", # Triple Financials Down
"FAS", # Triple Financials Up
"TBT", # 20 Treasury Bond Down
"TLT"] # 20 Treasury Bond Up
self.data = {}
for ticker in tickers:
symbol = self.AddEquity(ticker, Resolution.Daily).Symbol
self.data[symbol] = RateOfChangePercent(1)
consolidator = TradeBarConsolidator(CalendarType.Monthly)
self.RegisterIndicator(symbol, self.data[symbol], consolidator)
self.SetWarmUp(30)
self.TRIX_Period = 10
self.TRIX_OB =60 # Overbought is above 60
self.TRIX_OS =40 # Oversold is below 40
self.TRIX_Ind=self.TRIX("SPY",self.TRIX_Period)
# shcedule the function to fire on Tuesday, after 30 minutes
self.Schedule.On(
self.DateRules.MonthStart("TBT"),
self.TimeRules.AfterMarketOpen("TBT", 30),
self.Rebalance)
def OnData(self, data):
if self.TRIX_Ind.Current.Value > self.TRIX_OB:
self.Debug("Overbought Signal")
self.Liquidate()
self.TRIX_Ind = 0
elif self.TRIX_Ind.Current.Value < self.TRIX_OB:
self.Debug("Not Overbought")
return
def Rebalance(self):
if self.IsWarmingUp:
return
func = lambda x: x[1].Current.Value
selected = {x[0]: x[1].Current.Value
for x in sorted(self.data.items(), key=func, reverse=False)[:3]}
# liquidate the security which is no longer in the top3 momentum list
for symbol in self.data:
if symbol not in selected:
if self.Portfolio[symbol].Invested:
self.Liquidate(symbol, 'Not selected')
self.Notify.Email("mike_reichard@roadrunner.com", "Sell Trade Alert", "Sell")
self.Notify.Sms("19374430370", "Trade Executed - Sell")
for symbol in selected:
self.SetHoldings(symbol, 1/len(selected))
self.Notify.Email("mike_reichard@roadrunner.com", "Buy Trade Alert", "Buy:", symbol)
self.Notify.Sms("19374430370", "Trade Executed - Buy. Check your email!")