@backtrader thank you for the guidance. I read the documentation but I struggle to implement it.

Why it seems pointless and illogical? In fact many brokers give you a choice what to include in the bracket order (stop only, limit only, or stop/limit). What is wrong in having a stop to prevent you from excessive loss while working your own logic about the closing conditions.

Solved!

def next(self):

        for i, (d, d1) in enumerate(zip(self.m5_data, self.d1_data)):
            dt, (dn, d1n) = self.datetime.datetime(), (d._name, d1._name)

Great! thanks very much!

I simply created 2 new lists inside init

self.m5_data = self.datas[::2]
self.d1_data = self.datas[1::2]

self.inds = dict()
for i, d in enumerate(self.m5_data):
      self.inds[d] = dict()
      self.inds[d]['atr'] = bt.indicators.ATR(d, period=self.params.atr_per)
      self.inds[d]['stoch'] = bt.indicators.Stochastic(d, period=self.params.stoch_per,
                                    period_dslow=self.params.dslow_per)
self.daily_inds = dict()
for i, d in enumerate(self.d1_data):
      self.daily_inds[d] = dict()
      self.daily_inds[d]['d_atr'] = bt.indicators.ATR(d, period=self.params.d_atr_per)

Now however I've got trouble using it during next. For single time frame following code does the trick:

def next(self):

        for i, d in enumerate(self.datas):
            dt, dn = self.datetime.datetime(), d._name
            pos = self.getposition(d).size
            
            if pos==0:
                   # And then follows the logic of the strategy

but for multiple time frame i couldn't enumerate both lists simultaneously. I tried following

        for i, d in enumerate(zip(self.m5_data, self.d1_data)):
            dt, dn = self.datetime.datetime(), d._name
            pos = self.getposition(d).size
# and also
        for i, d in enumerate(self.m5_data + self.d1_data):
            dt, dn = self.datetime.datetime(), d._name
            pos = self.getposition(d).size

neither of them worked. Further ahead in the process I believe that time frames are matched by d._name and self.datetime.datetime, and they should not necessarily be enumerated simultaneously. What would be the solution here?

When I use a single time frame I have no trouble resampling my data and implementing it into init exactly the way its shown in the BT documantation:

def __init__(self):

        self.atr = bt.indicators.ATR(self.data, period=self.params.atr_per)
        self.stoch = bt.indicators.Stochastic(self.data, period=self.params.stoch_per,
            period_dslow=self.params.dslow_per)

        self.daily_atr = bt.indicators.ATR(self.data1, period=self.params.datr_per)

When I work with multiple data feed I use following code to add it to cerebro:

for i in range(len(symbols)):
    dataframe = pandas.read_csv(symbols[i][0], index_col=0, 
                                parse_dates=True, 
                                dayfirst=True
                                )
    data = PandasData(dataname=dataframe, timeframe=bt.TimeFrame.Minutes, compression=5)
    cerebro.adddata(data, name=symbols[i][1])

and then following code to implement it into init:

 def __init__(self):

        self.inds = dict()
        for i, d in enumerate(self.datas):
            self.inds[d] = dict()
            self.inds[d]['atr'] = bt.indicators.ATR(d, period=self.params.atr_per)
            self.inds[d]['stoch'] = bt.indicators.Stochastic(d, period=self.params.stoch_per,
                                    period_dslow=self.params.dslow_per)

The code above works perfectly witha single timeframe.

For a single datafeed and multiple timeframe, I have self.data for my intraday data and self.data1 for my daily data which I can pass to the indicators I want and from there on my strategy works as expected.

For multiple datafeeds however, looks like backtrader includes both the 5 min and daily timeframes in same set of feeds (self.datas) and from here on I cannot pass the data I want to the relevant indicators. Not only this but the daily data also messes around with my intraday indicators.

I tried to replicate the above code during init:

        self.daily_inds = dict()
        for i, d1 in enumerate(self.data1):
            self.daily_inds[d1] = dict()
            self.daily_inds[d1]['d_atr'] = bt.indicators.ATR(d1, period=5)

but it simply wouldnt work.

Is there a way to prevent daily data messing around with my intraday indicators and use it only for the calculation of the daily indicators?

Daily ATR is important to me as it presents the average daily range for the past few days.

thanks,
Rum

I've got following problem: Stop order is supposed to get cancelled automatically if Limit order is executed (also known as OCO) and position closed. In my strategy I do not use Limit order as my profitable positions are closed by the strategy logic. However, I cannot leave a position without a stop order. If I attach a stop or trailing stop and my trade is closed by the logic of the strategy, the stop order remains active and gets executed later. I need some help. I can't implement this part of the code.