| Overall Statistics |
|
Total Trades 7199 Average Win 0.15% Average Loss -0.11% Compounding Annual Return 41.337% Drawdown 47.000% Expectancy 0.327 Net Profit 235.168% Sharpe Ratio 1.129 Probabilistic Sharpe Ratio 45.146% Loss Rate 44% Win Rate 56% Profit-Loss Ratio 1.38 Alpha 0.478 Beta -0.308 Annual Standard Deviation 0.381 Annual Variance 0.145 Information Ratio 0.602 Tracking Error 0.456 Treynor Ratio -1.397 Total Fees $27293.96 Estimated Strategy Capacity $2300000.00 Lowest Capacity Asset ABX R735QTJ8XC9X |
class MACrossover(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2018, 1, 1) # Set Start Date
# self.SetEndDate(2020, 1, 1) # Set End Date
self.SetCash(100000) # Set Strategy Cash
# self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage)
self.stop = False
self.stocks = ["CSCO","TSLA", "JPM", "QCOM", "AMD", "TLT","QQQ"]
self.stocks_weight = {"CSCO":0.1, "TSLA":0.1, "JPM":0.1, "QCOM":0.1, "AMD":0.1, "TLT":0.1, "QQQ":0.1 }
self.AddEquity("CSCO", Resolution.Daily) # Networking hardware, software, telecommunications equipment
self.AddEquity("TSLA", Resolution.Daily) # Electric Cars, Solar & Clean Energy
self.AddEquity("JPM", Resolution.Daily) # Banking / Finance
self.AddEquity("QCOM", Resolution.Daily) # Semiconductor stock
self.AddEquity("AMD", Resolution.Daily) # Semiconductor stock
self.AddEquity("TLT", Resolution.Daily) # TLT is an etf of US Treasury bond
self.AddEquity("QQQ", Resolution.Daily) # QQQ is an etf that tracks Nasdaq index
self.AddEquity("GOLD", Resolution.Daily)
self.AddEquity("WMP", Resolution.Daily)
# Part 2 Step 2: Calculate Moving Averages
def OnData(self, data):
if self.stop:
return
stocks = self.stocks
for stock in stocks:
# self.Debug(stock)
stock_data = self.History ([stock], 30, Resolution.Daily)
MA_Fast_Pre = stock_data.close[25:30].mean()
MA_Slow_Pre = stock_data.close [9:30].mean()
#
# Part 3 Strategy: Make Crossover rule
#
# When slow sma < fast sma, buy the stock
if MA_Slow_Pre < MA_Fast_Pre:
self.Debug(self.stocks_weight[stock])
self.SetHoldings(stock, self.stocks_weight[stock])
self.SetHoldings("GOLD", 0.15)
self.SetHoldings("WMP", 0.15)
# When slow sma > fast sma, sell the stock
if MA_Slow_Pre > MA_Fast_Pre:
self.SetHoldings(stock, 0.3)
self.SetHoldings("GOLD", 0.35)
self.SetHoldings("WMP", 0.35)
# Part 4 Step 4: Make Drawdown stop
# if self.Portfolio.Cash < 0.85*1000:
# self.stop = True
# self.Liquidate()