Thanks @backtrader ! I will provide the code samples and history data as soon as I find a time.

Hi,
I exported the history data from my MT4 application and used them as data input for backtader.

My test strategy is trivial: Buy/Sell when two MAs cross over. The same simple algorithm is implemented in backtrader and MT4 and applied to the same data.

The results which I get using MT4 and backtrader are not same: sometimes the buy/sell operation is executed in the same time on both platforms but sometimes not (more often).

Does anybody have similar experience? What could be the reason?

Thanks!

@backtrader

python oandatest.py --token XXX --account XXX --data0 EUR_USD --timeframe Days

Strategy Created

Datetime, Open, High, Low, Close, Volume, OpenInterest, SMA
Traceback (most recent call last):
File "oandatest.py", line 481, in <module>
runstrategy()
File "oandatest.py", line 297, in runstrategy
cerebro.run(exactbars=args.exactbars)
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\cerebro.py",
line 810, in run
runstrat = self.runstrategies(iterstrat)
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\cerebro.py",
line 940, in runstrategies
self._runnext(runstrats)
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\cerebro.py",
line 1153, in _runnext
newqcheck = not any(d.haslivedata() for d in datas)
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\cerebro.py",
line 1153, in <genexpr>
newqcheck = not any(d.haslivedata() for d in datas)
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\feeds\oanda.p
y", line 255, in haslivedata
return bool(self._storedmsg or self.qlive) # do not return the objs
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\lineseries.py
", line 429, in getattr
return getattr(self.lines, name)
AttributeError: 'Lines_LineSeries_DataSeries_OHLC_OHLCDateTime_Abst' object has
no attribute '_storedmsg'

Hi,
when I run oandatest.py with minimum parameters (only token, account and data0) I get this error:

Traceback (most recent call last):
File "oandatest.py", line 481, in <module>
runstrategy()
File "oandatest.py", line 202, in runstrategy
timeframe = bt.TimeFrame.TFrame(args.timeframe)
File "D:\Anaconda3\envs\python3.4.5\lib\site-packages\backtrader\dataseries.py
", line 53, in TFrame
return getattr(cls, name)
AttributeError: type object 'TimeFrame' has no attribute ''

Any help? Thanks!

I am using 1min data for EURUSD, from the csv file. Data are read correctly and plotted fine.
Ia m also resampling these data to daily timeframe but something doesn't work correctly. I am getting peculiar chart for daily data.

In next() function I print this:

txt = ','.join(
            [self.data.datetime.date(0).isoformat() +" "
             + self.data.datetime.time(0).isoformat()+", 1min data (OHLC): "
            '%.5f' % self.data.open[0]+", "
            '%.5f' % self.data.high[0]+", "
            '%.5f' % self.data.low[0]+", "
            '%.5f' % self.data.close[0]+", Daily data (OHLC):"
            '%.5f' % self.data1.open[0]+", "
            '%.5f' % self.data1.high[0]+", "
            '%.5f' % self.data1.low[0]+", "
            '%.5f' % self.data1.close[0]
            ])

print(txt)

The excerpt of the output:

2016-01-04 15:53:00, 1min data (OHLC): 1.08115, 1.08151, 1.08112, 1.08147, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 15:54:00, 1min data (OHLC): 1.08146, 1.08151, 1.08122, 1.08128, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 15:55:00, 1min data (OHLC): 1.08128, 1.08133, 1.08113, 1.08131, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 15:56:00, 1min data (OHLC): 1.08135, 1.08146, 1.08104, 1.08118, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 15:57:00, 1min data (OHLC): 1.08117, 1.08148, 1.08079, 1.08083, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 15:58:00, 1min data (OHLC): 1.08082, 1.08083, 1.08037, 1.08048, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 15:59:00, 1min data (OHLC): 1.08048, 1.08054, 1.08012, 1.08015, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:00:00, 1min data (OHLC): 1.08016, 1.08046, 1.08016, 1.08046, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:01:00, 1min data (OHLC): 1.08045, 1.08048, 1.08021, 1.08037, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:02:00, 1min data (OHLC): 1.08039, 1.08099, 1.08037, 1.08097, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:03:00, 1min data (OHLC): 1.08098, 1.08123, 1.08064, 1.08076, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:04:00, 1min data (OHLC): 1.08076, 1.08093, 1.08064, 1.08085, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:05:00, 1min data (OHLC): 1.08085, 1.08102, 1.08021, 1.08022, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:06:00, 1min data (OHLC): 1.08016, 1.08062, 1.08016, 1.08062, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:07:00, 1min data (OHLC): 1.08060, 1.08060, 1.08011, 1.08032, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:08:00, 1min data (OHLC): 1.08031, 1.08047, 1.07985, 1.08000, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:09:00, 1min data (OHLC): 1.08000, 1.08059, 1.07998, 1.08050, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:10:00, 1min data (OHLC): 1.08050, 1.08051, 1.07998, 1.08007, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:11:00, 1min data (OHLC): 1.08008, 1.08013, 1.08000, 1.08002, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:12:00, 1min data (OHLC): 1.08006, 1.08009, 1.07992, 1.08003, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:13:00, 1min data (OHLC): 1.08003, 1.08005, 1.07873, 1.07884, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:14:00, 1min data (OHLC): 1.07885, 1.07912, 1.07846, 1.07855, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:15:00, 1min data (OHLC): 1.07855, 1.07871, 1.07841, 1.07854, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:16:00, 1min data (OHLC): 1.07853, 1.07886, 1.07847, 1.07852, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:17:00, 1min data (OHLC): 1.07852, 1.07879, 1.07850, 1.07861, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:18:00, 1min data (OHLC): 1.07861, 1.07865, 1.07835, 1.07846, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:19:00, 1min data (OHLC): 1.07848, 1.07860, 1.07824, 1.07836, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:20:00, 1min data (OHLC): 1.07836, 1.07857, 1.07826, 1.07848, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:21:00, 1min data (OHLC): 1.07848, 1.07868, 1.07840, 1.07860, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:22:00, 1min data (OHLC): 1.07862, 1.07866, 1.07820, 1.07820, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:23:00, 1min data (OHLC): 1.07821, 1.07841, 1.07816, 1.07818, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:24:00, 1min data (OHLC): 1.07818, 1.07829, 1.07812, 1.07818, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516
2016-01-04 16:25:00, 1min data (OHLC): 1.07818, 1.07853, 1.07815, 1.07848, Daily data (OHLC):1.08718, 1.08727, 1.08451, 1.08516

Resampling of 1min data is done with this command:

cerebro.resampledata(data, timeframe=bt.TimeFrame.Days)

What could be the problem here?

Actually, weekly indicator value is correct but the presentation on the graph is wrong.

The code is not perfect but you can reproduce the issue with it:

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

from datetime import datetime
import os.path 
import sys 

import backtrader as bt

class TestIndicator(bt.Indicator):
 
    lines = ('h', 'l')
    plotinfo = dict(subplot=False)
    
    params = (
        ('is_bars_aggregated', True),
        ('_autoplot', False),  # attempt to plot on real target data
    )
    
    
    def _plotinit(self):
        # Try to plot to the actual timeframe master
        if self.p._autoplot:
            if hasattr(self.data, 'data'):
                self.plotinfo.plotmaster = self.data.data

    def __init__(self):
        
              
        if self.p.is_bars_aggregated:
            high = self.data.high
            low = self.data.low
        else:
            high = self.data.high(-1)
            low = self.data.low(-1)            
        
        self.lines.h=high                
        self.lines.l=low
                
        if self.p._autoplot:
            self.plotinfo.plot = False  # disable own plotting
            self()  # Coupler to follow real object


        
class TestStrategy(bt.Strategy):
    
        
    def __init__(self):
        
        self.TIDaily = TestIndicator(self.data0, is_bars_aggregated=False, plot=False)
        self.TIWeekly = TestIndicator(self.data1, is_bars_aggregated=True, _autoplot=True, plot=False)
        self.TIMonthly = TestIndicator(self.data2, is_bars_aggregated=True, _autoplot=False, plot=False)
        
         

    def notify_order(self, order):
        pass
        

    def notify_trade(self, trade):
        pass

    def next(self):
        pass
        
  

if __name__ == '__main__':      
        
     
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)   

    data = bt.feeds.YahooFinanceData(dataname='^GSPC', fromdate=datetime(2016, 11, 1), todate=datetime(2016, 11, 30))
    
    data2=data.clone()
    data2.plotinfo.plot=False
    data3=data.clone()
    data3.plotinfo.plot=False
    
    cerebro.adddata(data)
    cerebro.resampledata(data2, timeframe=bt.TimeFrame.Weeks)    
    cerebro.resampledata(data3, timeframe=bt.TimeFrame.Months)
  
    cerebro.broker.setcash(10000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=1)
    # Set the commission        
    cerebro.broker.setcommission(commission=0.000)
    #cerebro.broker.setcommission(commission=7.0, margin=1000.0, mult=10.0)

    # 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())

    # Plot the result
    cerebro.plot(style='candle')

It can't be simpler :) Just calculate Low of the previous bar in an indicator for weekly or monthly data and show the indicator on daily data. That it what I showed for SP500, Low and High (blue and red line).

Ok, I put here what I got and what I think I should get. This example uses simple indicator which calculates high and low of the previous bar. Each bar on chart represents one trading day and the indicator is calculated for weekly data and plot on daily chart.
Weekly indicator should have the same value for the week November 7-11 but instead of that the same value is from November 8-14. I hope I managed to explain where is the problem.

This seems to be a bug or I don't understand something :(
I created an indicator similar to PivotPoint which uses the values from previous bar for the calculation.
My original data are daily data but I also resample to weekly and monthly.
When I plot my indicators on daily chart everything is fine for the indicator that works on daily data.
For the indicators that use resampled data (weekly&monthly), values seem not to be ok. For example, for weekly indicator, its value is changed each Tuesday, not Monday. Similar for monthly indicator, it changes its value not on the first trading day in the month but on the day after.
I am using last version of Backtrader.