| Overall Statistics |
|
Total Trades 49 Average Win 0.08% Average Loss 0% Compounding Annual Return 54.309% Drawdown 3.600% Expectancy 0 Net Profit 20.800% Sharpe Ratio 3.085 Probabilistic Sharpe Ratio 88.447% Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 0.528 Beta -0.082 Annual Standard Deviation 0.143 Annual Variance 0.02 Information Ratio -1.808 Tracking Error 0.341 Treynor Ratio -5.381 Total Fees $49.05 |
class GetCurrentPositions(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 2, 19) # Set Start Date
self.SetStartDate(2020, 3, 19) # Set Start Date
self.SetCash(100000) # Set Strategy Cash
self.SPYSecurity = self.AddEquity("SPY", Resolution.Daily)
self.isFirst = True
self.Schedule.On(self.DateRules.EveryDay(self.SPYSecurity.Symbol)
, self.TimeRules.AfterMarketOpen(self.SPYSecurity.Symbol, 1)
, self.__TestCB)
self.month = None
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
Arguments:
data: Slice object keyed by symbol containing the stock data
'''
if self.isFirst:
self.SetHoldings(self.SPYSecurity.Symbol, 0.5);
self.isFirst = False
num_holdings = len(self.Portfolio)
if num_holdings != 0:
for symbol, securityHolding in self.Portfolio.items():
self.SetHoldings(symbol, .5 / num_holdings)
# securityEquity = securityHolding.AveragePrice * securityHolding.Quantity
# securityEquity = securityHolding.AveragePrice * securityHolding.Quantity + securityHolding.TotalCloseProfit()
# self.Log("symbol: {} ratio: {}".format(symbol, securityEquity / self.Portfolio.TotalPortfolioValue))
# if not self.Portfolio.Invested:
# self.SetHoldings("SPY", 1)
def __TestCB(self):
if not self.month == self.Time.month:
self.month = self.Time.month
self.SetHoldings(self.SPYSecurity.Symbol, 0.5);
self.Log("After rebalance")