| Overall Statistics |
|
Total Orders 10001 Average Win 0.64% Average Loss -0.99% Compounding Annual Return 89.180% Drawdown 29.000% Expectancy 0.508 Start Equity 100000 End Equity 499579.20 Net Profit 399.579% Sharpe Ratio 1.758 Sortino Ratio 1.874 Probabilistic Sharpe Ratio 77.265% Loss Rate 9% Win Rate 91% Profit-Loss Ratio 0.65 Alpha 0.576 Beta 1.036 Annual Standard Deviation 0.362 Annual Variance 0.131 Information Ratio 1.937 Tracking Error 0.299 Treynor Ratio 0.615 Total Fees $1127.21 Estimated Strategy Capacity $45000000.00 Lowest Capacity Asset NFLX SEWJWLJNHZDX Portfolio Turnover 6.47% |
from AlgorithmImports import *
class EMAMovingAverageStrategy(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2018, 1, 1)
self.SetEndDate(2021, 1, 1)
self.SetCash(100000)
# Add all symbols in S&P 500
self.symbols = ["AAPL", "MSFT", "GOOGL", "AMZN", "FB", "JPM", "V", "PG", "DIS", "HD", # Add more symbols as needed
"VZ", "KO", "INTC", "NFLX", "TSLA", "NVDA", "UNH", "PYPL", "PEP", "ABT",
"BAC", "CMCSA", "ADBE", "XOM", "MRK", "PFE", "WMT", "NKE", "CSCO", "MCD",
"MA", "ABNB", "CRM", "AVGO", "T", "ORCL", "ACN", "CVX", "LMT", "MDT",
"IBM", "TXN", "QCOM", "LOW", "AMGN", "SBUX", "TMO", "COST", "GILD", "UPS"]
# Initialize indicators and rolling windows for each symbol
self.indicators = {}
for symbol in self.symbols:
equity = self.AddEquity(symbol, Resolution.Daily)
self.indicators[symbol] = {
"ema9": self.EMA(equity.Symbol, 9, Resolution.Daily),
"ema15": self.EMA(equity.Symbol, 15, Resolution.Daily),
"ema65": self.EMA(equity.Symbol, 65, Resolution.Daily),
"ema200": self.EMA(equity.Symbol, 150, Resolution.Daily),
"ema35": self.EMA(equity.Symbol, 35, Resolution.Daily),
"rsi": self.RSI(equity.Symbol, 14, Resolution.Daily)
}
self.WarmUpIndicator(symbol)
# Ensure the algorithm waits until all indicators are warmed up
self.SetWarmUp(200)
def WarmUpIndicator(self, symbol):
# Get historical data for warm-up
history = self.History(symbol, 210, Resolution.Daily)
# Warm up the indicators with historical data
for bar in history:
self.indicators[symbol]["ema9"].Update(bar.EndTime, bar.Close)
self.indicators[symbol]["ema15"].Update(bar.EndTime, bar.Close)
self.indicators[symbol]["ema65"].Update(bar.EndTime, bar.Close)
self.indicators[symbol]["ema200"].Update(bar.EndTime, bar.Close)
self.indicators[symbol]["ema35"].Update(bar.EndTime, bar.Close)
self.indicators[symbol]["rsi"].Update(bar.EndTime, bar.Close)
def OnData(self, data):
if self.IsWarmingUp:
return
for symbol in self.symbols:
if data.ContainsKey(symbol):
self.TradeSymbol(symbol)
def TradeSymbol(self, symbol):
indicators = self.indicators[symbol]
if self.IsBuyCondition(indicators):
self.SetHoldings(symbol, 1)
elif self.IsSellCondition(indicators):
self.Liquidate(symbol)
elif self.Portfolio[symbol].Invested:
if self.IsExitBuyCondition(indicators):
self.Liquidate(symbol)
elif self.IsExitSellCondition(indicators):
self.Liquidate(symbol)
def IsBuyCondition(self, indicators):
ema_condition = (indicators["ema9"].Current.Value > indicators["ema15"].Current.Value > indicators["ema65"].Current.Value > indicators["ema200"].Current.Value)
ema35_condition = indicators["ema35"].Current.Value > 60
return ema_condition and ema35_condition
def IsSellCondition(self, indicators):
ema_condition = (indicators["ema9"].Current.Value < indicators["ema15"].Current.Value < indicators["ema65"].Current.Value < indicators["ema200"].Current.Value)
ema35_condition = indicators["ema35"].Current.Value < 40
return ema_condition and ema35_condition
def IsExitBuyCondition(self, indicators):
ema_cross_condition = (indicators["ema9"].Current.Value < indicators["ema65"].Current.Value or indicators["ema15"].Current.Value < indicators["ema65"].Current.Value)
rsi_condition = indicators["rsi"].Current.Value < 40
return ema_cross_condition and rsi_condition
def IsExitSellCondition(self, indicators):
ema_cross_condition = (indicators["ema9"].Current.Value > indicators["ema65"].Current.Value or indicators["ema15"].Current.Value > indicators["ema65"].Current.Value)
rsi_condition = indicators["rsi"].Current.Value > 60
return ema_cross_condition and rsi_condition