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BacktestingRealTimeHandler.Run Error

New to Algo Trading and got this error when trying to back test...

BacktestingRealTimeHandler.Run(): There was an error in a scheduled event BTCUSD: EveryDay: BTCUSD: 1 min before MarketClose. The error was TypeError : unindexable object

 

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


from datetime import datetime
import decimal
import numpy as np
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Brokerages import *
from QuantConnect.Orders import *


class DynamicBreakoutAlgorithm(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2019,1,1)
self.SetEndDate(2019,5,9)
self.SetCash(100000)
self.SetCash("EUR", 10000)
self.SetCash("BTC", 1)
self.SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash)
self.AddCrypto("BTCUSD", Resolution.Daily)
self.syl = "BTCUSD"
self.Securities["BTCUSD"].SetDataNormalizationMode(DataNormalizationMode.Raw);
self.Schedule.On(self.DateRules.EveryDay(self.syl), self.TimeRules.BeforeMarketClose(self.syl,1),Action(self.SetSignal))
self.numdays = 20
self.ceiling,self.floor = 60,20
self.buypoint, self.sellpoint= None, None
self.longLiqPoint, self.shortLiqPoint, self.yesterdayclose= None, None, None
self.SetBenchmark(self.syl)
self.Bolband = self.BB(self.syl, self.numdays, 2, MovingAverageType.Simple, Resolution.Daily)

def SetSignal(self):

close = self.History(self.syl, 31, Resolution.Daily)['close']
todayvol = np.std(close[1:31])
yesterdayvol = np.std(close[0:30])
deltavol = (todayvol - yesterdayvol) / todayvol
self.numdays = int(round(self.numdays * (1 + deltavol)))

if self.numdays > self.ceiling:
self.numdays = self.ceiling
elif self.numdays < self.floor:
self.numdays = self.floor

self.high = self.History(self.syl, self.numdays, Resolution.Daily)['high']
self.low = self.History(self.syl, self.numdays, Resolution.Daily)['low']

self.buypoint = max(self.high)
self.sellpoint = min(self.low)
historyclose = self.History(self.syl, self.numdays, Resolution.Daily)['close']
self.longLiqPoint = np.mean(historyclose)
self.shortLiqPoint = np.mean(historyclose)
self.yesterdayclose = historyclose.iloc[-1]

# wait for our BollingerBand to fully initialize
if not self.Bolband.IsReady: return

holdings = self.Portfolio[self.syl].Quantity

if self.yesterdayclose > self.Bolband.UpperBand.Current.Value and self.Portfolio[self.syl].Price >= self.buypoint:
self.SetHoldings(self.syl, 1)
elif self.yesterdayclose < self.Bolband.LowerBand.Current.Value and self.Portfolio[self.syl].Price <= self.sellpoint:
self.SetHoldings(self.syl, -1)

if holdings > 0 and self.Portfolio[self.syl].Price <= self.shortLiqPoint:
self.Liquidate(self.syl)
elif holdings < 0 and self.Portfolio[self.syl].Price >= self.shortLiqPoint:
self.Liquidate(self.syl)

self.Log(str(self.yesterdayclose)+(" # of days ")+(str(self.numdays)))

def OnData(self,data):
pass

 

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Hi Liam,

Historical data requests require that you pass a Symbol object rather than a string to specify the security for which you are requesting data. History calls with work if you add/change these lines of code
 

## In initialize
self.symbolForHistoryCall = self.AddCrypto("BTCUSD", Resolution.Daily).Symbol

## In scheduled event
close = self.History(self.symbolForHistoryCall, 31, Resolution.Daily)['close']
self.high = self.History(self.symbolForHistoryCall, self.numdays, Resolution.Daily)['high']
self.low = self.History(self.symbolForHistoryCall, self.numdays, Resolution.Daily)['low']

Right now, our Crypto data has deprecated due to a vendor error, and we are working on getting it back up and running as quickly as possible. I had to modify the End Date of the algorithm to accommodate this, as a history call beyond 5/4/19 returns an empty data frame and will throw an error.

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


Update Backtest





0

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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