| Overall Statistics |
|
Total Trades 185 Average Win 4.00% Average Loss -0.90% Compounding Annual Return 8.932% Drawdown 16.900% Expectancy 1.248 Net Profit 210.300% Sharpe Ratio 0.765 Probabilistic Sharpe Ratio 15.032% Loss Rate 59% Win Rate 41% Profit-Loss Ratio 4.45 Alpha 0.08 Beta -0.012 Annual Standard Deviation 0.103 Annual Variance 0.011 Information Ratio -0.097 Tracking Error 0.215 Treynor Ratio -6.388 Total Fees $779.08 Estimated Strategy Capacity $1200000000.00 |
# SMA as support
class SMA_support(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2008, 1, 1)
self.SetCash(100000)
ma = 100
self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
self.support = self.SMA(self.symbol, ma, Resolution.Daily)
self.SetWarmUp(ma + 1)
def OnData(self, data):
price = self.Securities[self.symbol].Price
support = self.support.Current.Value
self.Plot('SMA', 'price', price)
self.Plot('SMA', 'support', support)
if price > support:
self.SetHoldings(self.symbol, 1)
else:
self.SetHoldings(self.symbol, 0)