Overall Statistics |

Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 |

from datetime import timedelta import math class MHAS(QCAlgorithm): def Initialize(self): self.SetStartDate(2019, 3, 1) # Set Start Date self.SetEndDate(2019, 3, 29) # Set End Date self.SetCash(100000) # Set Strategy Cash # subscribe SPY with minute level resolution self.AddEquity("SPY", Resolution.Daily) self.symbol_ = self.Symbol("SPY") self.Schedule.On(self.DateRules.Every(DayOfWeek.Saturday), self.TimeRules.At(0, 1), Action(self.endOfWeek)) def endOfWeek(self): # request data from last week hist = self.History(self.symbol_, timedelta(weeks = 1)) if hist.empty: # should only happen when data is broken return # build weekly bar high_price = max(hist['high']) low_price = min(hist['low']) open_price = hist['open'][0] close_price = hist['close'][len(hist.index) - 1] # reminder: logging price is limited to debugging purpose. Logging a bulk of data is against our term of use! self.Log(f"consolidated time: {self.Time}, open: {open_price}, high: {high_price}, low: {low_price}, close: {close_price}") # your strategy could be here: