Exception has occurred: ZeroDivisionError float division by zero
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Hi, When I try to add rsi to my intraday strategy , I am getting below error:
Exception has occurred: ZeroDivisionError float division by zero
File "F:\Learn\NR7\IBBackTradeLiveDataEx.py", line 160, in <module> cerebro.run()
What might be going wrong?#!/usr/bin/env python
-- coding: utf-8; py-indent-offset:4 --e
from future import absolute_import, division, print_function, unicode_literals
import backtrader as bt
from backtrader import Order
import matplotlib as plt
import datetime
import pytzclass IntraTrendStrategy(bt.Strategy):
def log(self, txt, dt=None): ''' Logging function fot this strategy''' dt = dt or self.datas[0].datetime.datetime(0) print('%s, %s' % (dt.isoformat(), txt)) def __init__(self): # Keep a reference to the "close" line in the data[0] dataseries self.dataclose = self.datas[0].close self.dataopen = self.datas[0].open self.datahigh = self.datas[0].high self.datalow = self.datas[0].low self.rsi = bt.indicators.RSI_SMA(self.dataclose, period=5) # To keep track of pending orders and buy price/commission self.order = None self.buyprice = None self.sellprice = None self.buycomm = None self.daylow = None self.dayhigh = None self.long = None def notify_order(self, order): if order.status in [order.Submitted, order.Accepted]: # Buy/Sell order submitted/accepted to/by broker - Nothing to do return # Check if an order has been completed # Attention: broker could reject order if not enough cash if order.status in [order.Completed]: if order.isbuy(): self.log( 'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' % (order.executed.price, order.executed.value, order.executed.comm)) self.buyprice = order.executed.price self.buycomm = order.executed.comm else: # Sell self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' % (order.executed.price, order.executed.value, order.executed.comm)) self.sellprice = order.executed.price self.bar_executed = len(self) elif order.status in [order.Canceled, order.Margin, order.Rejected]: self.log('Order Canceled/Margin/Rejected') self.order = None def notify_trade(self, trade): if not trade.isclosed: return self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' % (trade.pnl, trade.pnlcomm)) def next(self): # Simply log the closing price of the series from the reference self.log('%d Close, %.2f' % (len(self), self.dataclose[0])) if(self.data.datetime.time(0) == datetime.time(9,20)): self.daylow = self.datalow[0] self.dayhigh = self.datahigh[0] # Check if an order is pending ... if yes, we cannot send a 2nd one if self.order: if(self.data.datetime.time(0) == datetime.time(3,25)): self.order = None return # Check if we are in the market if not self.position: #add another condition as candle should be bullish if (self.data.datetime.time(0) == datetime.time(9,25) and self.rsi[0] < 50 and self.datalow[0] > self.dataopen[-1]): self.log('BUY CREATE, %.2f' % self.dataclose[0]) # Keep track of the created order to avoid a 2nd order #self.order = self.buy(exectype=Order.StopLimit, price=self.datahigh[0], valid=self.datas[0].datetime.date(0) + datetime.timedelta(days=3)) self.order = self.buy(size=1) self.long = True if (self.data.datetime.time(0) == datetime.time(9,25) and self.datahigh[0] < self.dataopen[-1]): self.log('SELL CREATE, %.2f' % self.dataclose[0]) # Keep track of the created order to avoid a 2nd order #self.order = self.buy(exectype=Order.StopLimit, price=self.datahigh[0], valid=self.datas[0].datetime.date(0) + datetime.timedelta(days=3)) self.order = self.sell(size=1) self.long = False else: # Already in the market ... we might sell if(self.long): target = self.buyprice + ((self.buyprice - self.daylow) * 2) if (self.data.datetime.time(0) == datetime.time(15,25) or self.dataclose[0]>=target or self.datalow[0] < self.daylow): # SELL, SELL, SELL!!! (with all possible default parameters) self.log('SELL CREATE, %.2f' % self.dataclose[0]) # Keep track of the created order to avoid a 2nd order self.order = self.sell(size=1) else: target = self.sellprice - ((self.dayhigh-self.sellprice) * 2) if (self.data.datetime.time(0) == datetime.time(15,25) or self.dataclose[0]<=target or self.datahigh[0] > self.dayhigh): # SELL, SELL, SELL!!! (with all possible default parameters) self.log('BUY CREATE, %.2f' % self.dataclose[0]) # Keep track of the created order to avoid a 2nd order self.order = self.buy(size=1)Create a cerebro entity
cerebro = bt.Cerebro()
store = bt.stores.IBStore(host="127.0.0.1", port=7496, clientId= 4)
Add a strategy
cerebro.addstrategy(IntraTrendStrategy)
stockkwargs = dict(
timeframe=bt.TimeFrame.Minutes,
rtbar=False, # use RealTime 5 seconds bars
historical=True, # only historical download
qcheck=0.5, # timeout in seconds (float) to check for events
fromdate=datetime.datetime(2020, 1, 1), # get data from..
todate=datetime.datetime(2020, 9, 20), # get data from..
latethrough=False, # let late samples through
tradename=None, # use a different asset as order target
tz="Asia/Kolkata"
)data0 = store.getdata(dataname="TCS-STK-NSE-INR", **stockkwargs)
cerebro.resampledata(data0, timeframe=bt.TimeFrame.Minutes, compression=5)Set our desired cash start
cerebro.broker.setcash(100000.0)
Set the commission - 0.1% ... divide by 100 to remove the %
cerebro.broker.setcommission(commission=0.001)
Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
Run over everything
cerebro.run()
Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
#cerebro.plot(style='candlestick') -
Please ignore I was able to solve it
