@run-out Alright I got all the problems fixed for now. Thank you very much for your help and the fast answers.

@run-out I fixed it by also adding the buy and sell statements into the for loop in next. However the buys and sells still don´t get displayed in the plot and it doesn´t seem to buy and sell everytime the price is above/under the top/bot-band. So my main problem right now is the plot missing the buys and sells.
Thats my current code:

import backtrader as bt
import backtrader.feeds as btfeed
import datetime


# from datetime import datetime

class dataFeed(btfeed.GenericCSVData):
    params = (
        ('dtformat', '%Y-%m-%d %H:%M:%S'),
        ('datetime', 0),
        ('open', 1),
        ('high', 2),
        ('low', 3),
        ('close', 4),
        ('volume', 5),
        ('openinterest', -1)
    )


class firstStrategy(bt.Strategy):
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):

        # self.dataclose = self.datas[0].close

        self.bb_inds = dict()
        for d in self.datas:
            bb = bt.ind.BollingerBands(d, period=21, devfactor=2.0,
                                       movav=bt.ind.MovAv.Simple)
            self.bb_inds[d] = dict()
            self.bb_inds[d]["bb_top"] = bb.top
            self.bb_inds[d]["bb_bot"] = bb.bot


    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, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order

        self.order = None

    def next(self):
        for d in self.datas:
            dt, dn = self.datetime.date(), d._name
            pos = self.getposition(d).size
            # Simply log the closing price of the series from the reference
           # self.log('Close, %.2f' % d.close[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        # if self.order:
        #   return

        # Check if we are in the market
        #if not self.position:
            if d.close[0] < self.bb_inds[d]["bb_bot"][0]:

                # current close less than previous close

                # if self.dataclose[-1] < self.dataclose[-2]:
                # previous close less than the previous close

                # BUY, BUY, BUY!!! (with default parameters)
                self.log('BUY CREATE, %.2f' % d.close[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.buy()
                self.buy(data=d)

            # Already in the market ... we might sell
            if d.close[0] > self.bb_inds[d]["bb_top"][0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % d.close[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.sell()
                self.sell(data=d)


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()
    startcash = 10000

    # Add a strategy
    cerebro.addstrategy(firstStrategy)
#    cerebro.addindicator(BollingerBands)

    datalist = [("AM.ATVI.csv"), ("AM.MO.csv"), ("AM.GM.csv"), ("AM.CL.csv")]

    for i in range(len(datalist)):
        data = dataFeed(dataname=datalist[i], timeframe=bt.TimeFrame.Minutes, compression=1)
        cerebro.adddata(data, name=datalist[i])

    # Set our desired cash start
    cerebro.broker.setcash(startcash)

    # Set the commission
    # cerebro.broker.setcommission(commission=0.0005)

    # Add a sizer
    # cerebro.addsizer(bt.sizers.PercentSizer, percents=50)

    cerebro.run()
    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % startcash)

    # Get final portfolio Value
    portvalue = cerebro.broker.getvalue()
    pnl = portvalue - startcash

    # Print out the final result
    print('Final Portfolio Value: ${}'.format(portvalue))
    print('P/L: ${}'.format(pnl))
    cerebro.plot()

My plot:

@run-out Thank you very much, that helps a lot. Now there is still the problem that the buy and sell signals dont really work. It seems like the order is created for stock1 but executed for stock2. When I use your code from above with my CSV Datafiles and i dont log the closing price but only the orders this is my output:

2021-02-18, BUY CREATE, 43.76
2021-02-18, BUY EXECUTED, 101.03
Starting Portfolio Value: 10000.00
Final Portfolio Value: $10001.244999999999
P/L: $1.2449999999989814

Furthermore the buys and sells dont get displayed in the plot. Unfortunately I can´t find the mistake/s.

Fixed it.

@run-out Alright I got all the problems fixed for now. Thank you very much for your help and the fast answers.

Even though the buy and sell signals get triggered it seems like the orders get executed delayed or whatever. Here is my code for init and next:

    def __init__(self):

        # self.dataclose = self.datas[0].close

        self.bb_inds = dict()
        for d in self.datas:
            bb = bt.ind.BollingerBands(d, period=21, devfactor=2.0,
                                       movav=bt.ind.MovAv.Simple)
            self.bb_inds[d] = dict()
            self.bb_inds[d]["bb_top"] = bb.top
            self.bb_inds[d]["bb_bot"] = bb.bot


    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, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order

        #self.order = None

    def next(self):
        for d in self.datas:
            dt, dn = self.datetime.date(), d._name
            pos = self.getposition(d).size
            # Simply log the closing price of the series from the reference
           # self.log('Close, %.2f' % d.close[0])

        # Check if we are in the market
        #if not self.position:
            if d.close[0] < self.bb_inds[d]["bb_bot"][0]:

                # BUY, BUY, BUY!!! (with default parameters)
                self.log('BUY CREATE, %.2f' % d.close[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.buy()
                self.buy(data=d, size=1, price=d.close[0])

            # Already in the market ... we might sell
            if d.close[0] > self.bb_inds[d]["bb_top"][0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % d.close[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.sell()
                self.sell(data=d, size=1, price=d.close[0])

The plot:

@run-out I fixed it by also adding the buy and sell statements into the for loop in next. However the buys and sells still don´t get displayed in the plot and it doesn´t seem to buy and sell everytime the price is above/under the top/bot-band. So my main problem right now is the plot missing the buys and sells.
Thats my current code:

import backtrader as bt
import backtrader.feeds as btfeed
import datetime


# from datetime import datetime

class dataFeed(btfeed.GenericCSVData):
    params = (
        ('dtformat', '%Y-%m-%d %H:%M:%S'),
        ('datetime', 0),
        ('open', 1),
        ('high', 2),
        ('low', 3),
        ('close', 4),
        ('volume', 5),
        ('openinterest', -1)
    )


class firstStrategy(bt.Strategy):
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):

        # self.dataclose = self.datas[0].close

        self.bb_inds = dict()
        for d in self.datas:
            bb = bt.ind.BollingerBands(d, period=21, devfactor=2.0,
                                       movav=bt.ind.MovAv.Simple)
            self.bb_inds[d] = dict()
            self.bb_inds[d]["bb_top"] = bb.top
            self.bb_inds[d]["bb_bot"] = bb.bot


    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, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order

        self.order = None

    def next(self):
        for d in self.datas:
            dt, dn = self.datetime.date(), d._name
            pos = self.getposition(d).size
            # Simply log the closing price of the series from the reference
           # self.log('Close, %.2f' % d.close[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        # if self.order:
        #   return

        # Check if we are in the market
        #if not self.position:
            if d.close[0] < self.bb_inds[d]["bb_bot"][0]:

                # current close less than previous close

                # if self.dataclose[-1] < self.dataclose[-2]:
                # previous close less than the previous close

                # BUY, BUY, BUY!!! (with default parameters)
                self.log('BUY CREATE, %.2f' % d.close[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.buy()
                self.buy(data=d)

            # Already in the market ... we might sell
            if d.close[0] > self.bb_inds[d]["bb_top"][0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % d.close[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.sell()
                self.sell(data=d)


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()
    startcash = 10000

    # Add a strategy
    cerebro.addstrategy(firstStrategy)
#    cerebro.addindicator(BollingerBands)

    datalist = [("AM.ATVI.csv"), ("AM.MO.csv"), ("AM.GM.csv"), ("AM.CL.csv")]

    for i in range(len(datalist)):
        data = dataFeed(dataname=datalist[i], timeframe=bt.TimeFrame.Minutes, compression=1)
        cerebro.adddata(data, name=datalist[i])

    # Set our desired cash start
    cerebro.broker.setcash(startcash)

    # Set the commission
    # cerebro.broker.setcommission(commission=0.0005)

    # Add a sizer
    # cerebro.addsizer(bt.sizers.PercentSizer, percents=50)

    cerebro.run()
    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % startcash)

    # Get final portfolio Value
    portvalue = cerebro.broker.getvalue()
    pnl = portvalue - startcash

    # Print out the final result
    print('Final Portfolio Value: ${}'.format(portvalue))
    print('P/L: ${}'.format(pnl))
    cerebro.plot()

My plot:

@hexabraum I just tested it with more than 2 Stocks and it seems like only the very first stock in the ticker list gets bought or sold even though the order was created for another stock.

@run-out Thank you very much, that helps a lot. Now there is still the problem that the buy and sell signals dont really work. It seems like the order is created for stock1 but executed for stock2. When I use your code from above with my CSV Datafiles and i dont log the closing price but only the orders this is my output:

2021-02-18, BUY CREATE, 43.76
2021-02-18, BUY EXECUTED, 101.03
Starting Portfolio Value: 10000.00
Final Portfolio Value: $10001.244999999999
P/L: $1.2449999999989814

Furthermore the buys and sells dont get displayed in the plot. Unfortunately I can´t find the mistake/s.

@run-out Thanks but that doesn´t really help me. My problem is that the Bollinger Bands only work for my first data feed and also only get plotted for my first datafeed. Therefore the other securities are not in consideration to be bought or sold.

@run-out 4 securities equal one backtest, however each datafeed gets a technical analysis and therefore buy or sell signals for this exact security. I want the backtrader to backtest my strategy on multiple datafeeds. I hope that i got the point :D

The Bollinger Bands work for the first Data File, so it´s the only one where Orders are created.
Additionally the buys and sells dont get displayed, Where is the mistake?
Thanks for your help :)

import backtrader as bt
import backtrader.feeds as btfeed
from datetime import datetime

class dataFeed(btfeed.GenericCSVData):
    params = (
        ('dtformat', '%Y-%m-%d %H:%M:%S'),
        ('datetime', 0),
        ('open', 1),
        ('high', 2),
        ('low', 3),
        ('close', 4),
        ('volume', 5),
        ('openinterest', -1)
    )

class BollingerBands(bt.Indicator):
    lines = ('topband', 'botband')
    params = (('period', 21), ('devfactor', 2.0), ('movav', bt.ind.MovAv.Simple),)

    plotinfo = dict(subplot=False)

    def _plotlabel(self):
        plabels = [self.p.period, self.p.devfactor]
        plabels += [self.p.movav] * self.p.notdefault('movav')
        return plabels

    def __init__(self):
        bb = bt.ind.BollingerBands(
            period=self.p.period, devfactor=self.p.devfactor, movav=self.p.movav)

class firstStrategy(bt.Strategy):
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.dataclose = self.datas[0].close
        bb = bt.ind.BollingerBands(
            period=21, devfactor=2.0, movav=bt.ind.MovAv.Simple)
        self.lines.topband = bb.top
        self.lines.botband = bb.bot


    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, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order
        #self.order = None

    def next(self):
        for d in self.datas:
            dt, dn = self.datetime.date(), d._name
            pos = self.getposition(d).size
            # Simply log the closing price of the series from the reference
            self.log('Close, %.2f' % d.close[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        #if self.order:
        #   return

        # Check if we are in the market
        if not self.position:
            if self.dataclose[0] < self.lines.botband[0]:
                # current close less than previous close

                # if self.dataclose[-1] < self.dataclose[-2]:
                # previous close less than the previous close

                # BUY, BUY, BUY!!! (with 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()

            # Already in the market ... we might sell
            if self.dataclose[0] > self.lines.topband[0]:
                # 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()


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()
    startcash = 10000

    # Add a strategy
    cerebro.addstrategy(firstStrategy)
    cerebro.addindicator(BollingerBands)

    datalist = [("AM.ATVI.csv"), ("AM.MO.csv"), ("AM.GM.csv"), ("AM.CL.csv")]
    """  , ("AM.FDX.csv"), ("AM.NAKD.csv"), ("AM.NVDA.csv"), ("AM.OCGN.csv"), ("AM.ON.csv")
        , ("AM.PDD.csv"), ("AM.PLUG.csv"), ("AM.QCOM.csv"), ("AM.MDLZ.csv"), ("AM.ADP.csv")
        , ("AM.C.csv"), ("AM.AZN.csv"), ("AM.PEP.csv"), ("AM.ORCL.csv"), ("AM.QTT.csv")
        , ("AM.RUN.csv"), ("AM.SABR.csv"), ("AM.SNDL.csv"), ("AM.TSLA.csv"), ("AM.UAL.csv")
        , ("AM.UXIN.csv"), ("AM.WEN.csv"), ("AM.WFC.csv"), ("AM.YY.csv"), ("AM.ZNGA.csv")
        , ("AM.MSFT.csv"), ("AM.AAPL.csv"), ("AM.FB.csv"), ("AM.BABA.csv"), ("AM.TSM.csv")
        , ("AM.V.csv"), ("AM.JPM.csv"), ("AM.JNJ.csv")
        , ("AM.PG.csv"), ("AM.BAC.csv"), ("AM.INTC.csv"), ("AM.VZ.csv"), ("AM.NKE.csv")
        , ("AM.XOM.csv"), ("AM.KO.csv"), ("AM.T.csv"), ("AM.PFE.csv")
        , ("AM.MRK.csv"), ("AM.MS.csv"), ("AM.AAL.csv"), ("AM.GT.csv"), ("AM.UBER.csv")
        , ("AM.AMD.csv"), ("AM.PDD.csv"), ("AM.CVX.csv")]"""
#the files are located in my python project
    for i in range(len(datalist)):
        data = dataFeed(dataname=datalist[i], timeframe=bt.TimeFrame.Minutes, compression=60)
        cerebro.adddata(data, name=datalist[i])

    # Set our desired cash start
    cerebro.broker.setcash(startcash)

    # Set the commission
    #cerebro.broker.setcommission(commission=0.0005)

    # Add a sizer
    #cerebro.addsizer(bt.sizers.PercentSizer, percents=50)

    cerebro.run()
    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % startcash)

    # Get final portfolio Value
    portvalue = cerebro.broker.getvalue()
    pnl = portvalue - startcash

    # Print out the final result
    print('Final Portfolio Value: ${}'.format(portvalue))
    print('P/L: ${}'.format(pnl))
    cerebro.plot()

@hexabraum i fixed it by deleting the for loop in the log function.