Topics created by Jens Halsberghe

I agree and I understand the logic. I can't replay but also, it's useful to use target.activate() and it can be used to do only in certain scenarios where it looks most likely the target would have been hit. for example if the price never even reached the stoploss but got to the entry and then the target, it's perfectly fine to use it. in case of a big outside bar which would hit all three entry, target and stoploss there would be doubt but it's more an exceptional case.

thanks again for your help Dasch

I am still using backtrader. For simple stuff I write stuff directly using the oanda api.

In next you have assigend your entry order object to the variable self.order. When in notify_order, you access the current order object using the variable order. These are both order objects.

In an order object you can access the status of that object which is stores as in next self.order.status or in notify_order as order.status.

For completed orders this status variable will equal 4.

In your code, in next, you can use:

if self.order.status != self.order.Completed etc.

or

if self.order.status != 4 etc.

The cancel is normal. It is cancelling the other side of the bracket, so if you fill on the take profit, the stop gets cancelled and vice versa. If you want a bit more information in your log you can show the order reference numbers.

Also as another side note, I notice you are assigning the size using order.size. Size is acutally tracked in order.created.size.

A further update. I've simplified it further. the order is now being cancelled as it should. The execution is also fine bar one last problem. If the bar where the trade gets entered also hits the target, it doesn't execute the buy and sell on the same bar. I don't see how this can be achieved.

class Order_testing(bt.Strategy): params = dict( pfast=10, # period for the fast moving average pslow=30 # period for the slow moving average ) def log(self, txt, dt=None): ''' Logging function for this strategy''' dt = dt or self.datas[0].datetime.datetime(0) print('%s, %s' % (dt.strftime("%Y-%m-%d %H:%M"), txt)) def __init__(self): sma1 = bt.ind.SMA(period=self.p.pfast) # fast moving average sma2 = bt.ind.SMA(period=self.p.pslow) # slow moving average self.crossover = bt.ind.CrossOver(sma1, sma2) # crossover signal # To keep track of pending orders and buy price/commission self.order = None self.buyprice = None self.buycomm = 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: %.5f, Cost: %.f, 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: %.5f, Cost: %.f, Comm %.2f' % (order.executed.price, order.executed.value, order.executed.comm)) 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 %.5f, NET %.5f' % (trade.pnl, trade.pnlcomm)) def next(self): # Check if an order is pending ... if yes, we cannot send a 2nd one if self.order: if self.order.status == 2 and len(self) == self.bar_order_submitted + 1: self.broker.cancel(self.order) self.log("order was cancelled") # Check if we are in the market if not self.position: # Not yet ... we MIGHT BUY if ... if self.crossover > 0: # if fast crosses slow to the upside self.order = self.buy(exectype=bt.Order.StopLimit, price=self.data.high[0], transmit=False) self.StopLoss = self.sell(price=self.data.low[0],exectype=bt.Order.Stop, transmit=False, size=self.order.size,parent=self.order) self.target = self.sell(price=(self.data.high[0]-self.data.low[0])*1.1+self.data.high[0], exectype=bt.Order.Limit, transmit=True, size=self.order.size, parent=self.order) self.bar_order_submitted = len(self) self.log('BUY CREATE, %.5f' % self.order.price) self.log('SL: %.5f, T: %.5f' %(self.StopLoss.price,self.target.price)) if __name__ == '__main__': cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(Order_testing) # Create a Data Feed data = bt.feeds.PandasData(dataname=df2020) one_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=1) # cerebro.adddata(data) # Add a FixedSize sizer according to the stake cerebro.addsizer(bt.sizers.PercentSizer, percents=5000) #Add Analyzer cerebro.addanalyzer(bt.analyzers.PyFolio) cerebro.broker.setcommission(commission=0.0,leverage=500) # Set our desired cash start cerebro.broker.setcash(1000000.0) # Print out the starting conditions print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) HG = cerebro.run() # Print out the final result print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

below is a copy of the log again. It should sell at 06:29.

2020-08-12 06:28, BUY CREATE, 1.17185 2020-08-12 06:28, SL: 1.17171, T: 1.17200 2020-08-12 06:29, BUY EXECUTED, Price: 1.17185, Cost: 49324578, Comm 0.00 2020-08-12 06:30, SELL EXECUTED, Price: 1.17203, Cost: 49324578, Comm 0.00 2020-08-12 06:30, Order Canceled/Margin/Rejected 2020-08-12 06:30, OPERATION PROFIT, GROSS 7576.41679, NET 7576.41679

Have a look at my post here.

@Jens-Halsberghe But in next(), you get a single OHLC bar which is a plain Python object, you can use math.log in def next()

@dasch said in Resampling issues + adding multiple timeframes:

there are a lot of shortcuts to different lines, which are not used that much in examples, so it would only make sense to use them, when you know what you are doing.

I totally agree.

I found a better way:
just add a movav parameter when you use the ATR indicator like this:
bt.indicators.AverageTrueRange(self.data0, period=20, movav=MovAv.Simple)

I meant of course 1 for uptrend, -1 for downtrend but I can't edit my post

You may take a look at the _Bar class as an example (it is an internal class in Backtrader) and create something similar for your needs.

IB is the brokerage company, not data provider. This is not their business. Common approach is to get data from the data providers for backtests.

@run-out that is smart,thanks