Hi All,

Havn't been here in a while, glad to see the community is still active.

I have 2 data feeds (1-minute and 5-minute data) with 4 unique tickers.

I can't seem to figure out how to buy solely based on the 1-minute data.

Having gone through the docs, it was indicated that I need to do something like "self.buy(data=self.datas[0])", however, when I do this, the script only buys stock for the first ticker.

Any insight is greatly appreciated.

Alfred

import backtrader as bt
import datetime
from collections import defaultdict

#https://community.backtrader.com/topic/2306/easier-way-to-access-active-orders

class FixedCommisionScheme(bt.CommInfoBase):
    '''
    This is a simple fixed commission scheme
    '''
    params = (
        ('commission', 0.0075),
        ('stocklike', True),
        ('commtype', bt.CommInfoBase.COMM_FIXED),
        )

    def _getcommission(self, size, price, pseudoexec):
        commission = self.p.commission * abs(size)
        return commission 

class MyStrategy(bt.Strategy):
       
    params = (('sma1', 40),('sma2', 10))

    def __init__(self):
       
      

        self.order = {}

        self.sma1 = {}
        self.sma2 = {}
        
        for i, d in enumerate(self.datas):   
        
            sma1 = bt.indicators.SimpleMovingAverage(self.datas[i], period=self.params.sma1)       
            sma2 = bt.indicators.SimpleMovingAverage(self.datas[i], period=self.params.sma2)      
        
            self.sma1[d] = sma1
            self.sma2[d] = sma2
            
    def log(self, txt, dt=None):
        dt = self.datetime.datetime()
        print(f'{dt.isoformat()} {txt}') 

    
    def notify_order(self, order):
        #self.order[order.data._name] = None
        if order.status in [order.Completed, order.Margin]:
        
            if order.isbuy():
                self.log(f'-BUY  EXECUTED- Price: {order.executed.price:.2f} Comm: {order.executed.comm:.4f}, {order.data._name}')
            else:
                self.log(f'-SELL EXECUTED- Price: {order.executed.price:.2f} Comm: {order.executed.comm:.4f}, {order.data._name}')

    
    
    def notify_trade(self, trade):
        dt = self.data.datetime.datetime()
        if trade.isclosed:
            print('{} {} Closed: PnL Gross {}, Net {}'.format(
                                                dt,
                                                trade.data._name,
                                                round(trade.pnl,2),
                                                round(trade.pnlcomm,2)))
 
    
    def next(self):
        
        for i, d in enumerate(self.datas):

        
            pos = self.getposition(d).size

            

            if not pos:
                if d.close > self.sma2[d][0]:
                    self.buy(data=d,size=1)

            if pos:
                if d.close < self.sma2[d][0]:
                    self.close(data=d)

       
#Instantiate Cerebro engine
cerebro = bt.Cerebro()
#Set cash
cerebro.broker.setcash(100000.0)
#Set commissions
comminfo = FixedCommisionScheme()
cerebro.broker.addcommissioninfo(comminfo)
#Add strategy to Cerebro
cerebro.addstrategy(MyStrategy)
#Add data feeds
symbols = ['AA','MSFT','IBM','AMZN']

for symbol in symbols:

    #Add data
    data = bt.feeds.InfluxDB(host='localhost', port='8086',
                            username='root',
                            password='root',
                            database='test_data4',
                            dataname=symbol,
                            timeframe=bt.TimeFrame.Minutes, 
                            compression=1,
                            fromdate=datetime.datetime(2021, 12, 1),
                            todate=datetime.datetime(2021, 12, 23), 
                            dtformat=("%Y-%m-%d %H:%M:%S"),
                            high='high',
                            low='low',
                            open='open',
                            close='close',
                            volume='volume',
                            ointerest='openinterest')


    cerebro.adddata(data,name=symbol) 

    
    #Add data
    data1 = bt.feeds.InfluxDB(host='localhost', port='8086',
                            username='root',
                            password='root',
                            database='test_data4',
                            dataname=symbol,
                            timeframe=bt.TimeFrame.Minutes, 
                            compression=5,
                            fromdate=datetime.datetime(2021, 12, 1),
                            todate=datetime.datetime(2021, 12, 23), #add 1 extra day 
                            dtformat=("%Y-%m-%d %H:%M:%S"),
                            high='high',
                            low='low',
                            open='open',
                            close='close',
                            volume='volume',
                            ointerest='openinterest')
    

    cerebro.adddata(data1,name=symbol) 
   

#Begining portfolio value
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
#Run Cerebro Engine
cerebro.run()
#Ending portfolio value
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
#And plot it with a single command
cerebro.plot()