| Overall Statistics |
|
Total Trades 6 Average Win 0% Average Loss 0% Compounding Annual Return 0.007% Drawdown 0.000% Expectancy 0 Net Profit 0% Sharpe Ratio 0.285 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.001 Beta 0.001 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -8.711 Tracking Error 0.086 Treynor Ratio 0.049 Total Fees $6.00 |
from QuantConnect.Data.Market import TradeBar
from QuantConnect import Securities
class testyou(QCAlgorithm):
def Initialize(self):
# Set the cash we'd like to use for our backtest
# This is ignored in live trading
self.SetCash(100000)
# Start and end dates for the backtest.
# These are ignored in live trading.
self.SetStartDate(2012,1,1)
self.SetEndDate(2012,1,11)
self.sym="SPY"
# Add assets you'd like to see
self.spy = self.AddEquity(self.sym, Resolution.Daily).Symbol # for Alex code for tick values.. to use minimum tick values need to remove .Symbol
# ROR..
self.count = 0 # My counter
self.rWindow = RollingWindow[TradeBar](2) # Rolling window (yesterday value)
# Symbol properties..
#self.p = self.spy.SymbolProperties.MinimumPriceVariation
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
self.Log(">>> OnData called..")
#self.Log("tick size = " + str(self.p))
# Add SPY TradeBar in rollling window
self.rWindow.Add(data[self.sym])
bar = data[self.sym]
# Place open and close orders..
self.MarketOnOpenOrder(self.sym, 1, "hello")
self.MarketOnCloseOrder(self.sym, -1, "goodbye")
self.Log("OnData exited >>>")
self.Log(" ")