| 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 Probabilistic 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 -0.094 Tracking Error 0.385 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
from datetime import timedelta
from QuantConnect.Data.UniverseSelection import *
from Selection.FundamentalUniverseSelectionModel import FundamentalUniverseSelectionModel
from System.Drawing import Color
######################################################27
class runLevels(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 2, 13)
self.SetEndDate(2020, 7, 29)
self.SetCash(100000)
self.AddEquity("AMD", Resolution.Minute)
self.Consolidate("AMD", Resolution.Daily, self.DailyConsolidated)
self.Schedule.On(self.DateRules.On(2020, 7, 29), self.TimeRules.At(13, 0), self.LastDay)
self.ConsolidatedBars=[]
def OnData(self, data):
pass
def DailyConsolidated(self, bar):
self.ConsolidatedBars.append(bar)
def LastDay(self):
self.history = self.History(self.Symbol("AMD"), len(self.ConsolidatedBars), Resolution.Daily)
self.Debug(len(self.ConsolidatedBars))
for i in range(0,len(self.ConsolidatedBars)):
historicSlice = self.history.iloc[i]
HistoricBar = TradeBar(historicSlice.name[1], self.Symbol("AMD"), historicSlice.open, historicSlice.high, historicSlice.low, historicSlice.close, historicSlice.volume)
ConsolidatedBar = self.ConsolidatedBars[i]
if abs(HistoricBar.High - self.ConsolidatedBars[i].High) > 0.02 or abs(HistoricBar.Low - self.ConsolidatedBars[i].Low) > 0.02:
self.Log(f"HISTORIC T:{HistoricBar.EndTime} H: {HistoricBar.High} L:{HistoricBar.Low} CONSOLIDATED T:{ConsolidatedBar.EndTime} H: {ConsolidatedBar.High} L:{ConsolidatedBar.Low}")