| 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 |
# CryptoVolatilityTap (v4, ETHUSD, Minute, Py)
# Tap crypto volatility spikes
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Indicators")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Data import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from QuantConnect.Data.Consolidators import *
from datetime import datetime
import decimal as d
import numpy as np
class CVTap(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2017,11,1) #Set Start Date
self.SetEndDate(2017,11,14) #Set End Date
self.SetCash(10000) #Set Strategy Cash
self.fxPair = "EURUSD"
# Add EURUSD
self.AddForex(self.fxPair, Resolution.Minute)
# Create consolidator for 30 minutes
consThirtyMin = QuoteBarConsolidator(30)
consThirtyMin.DataConsolidated += self.OnDataConsolidated
self.SubscriptionManager.AddConsolidator(self.fxPair, consThirtyMin)
self.bb30 = BollingerBands("30minBB", 20,2,MovingAverageType.Simple)
# Inititalize rolling window which stores to store upper bollinger band indicator values
self.bbUpperRollingWindow = RollingWindow[float](3)
def OnDataConsolidated(self, sender, bar):
# Update bb30 indicator
self.bb30.Update(bar.EndTime, bar.Close)
# Add to rolling window
self.bbUpperRollingWindow.Add(self.bb30.Current.Value)
def OnData(self, data):
# Return if rolling window is not ready
if not self.bbUpperRollingWindow.IsReady: return
self.Log("upper rolling window : " + str(self.bbUpperRollingWindow[0]))