Hi,
I'm pretty new to backtrader. I've read through the manual but haven't found the answer yet to a question I have. Is there a way to retrieve everything you feed into backtrader as a dataframe.
for example, we feed OHLC data into backtrader, we create 2 moving averages, we add a long and short signal when crossing over etc.
Is there a way to then also get all this information in a dataframe? eg the columns would look something like:
Date, Open, High, Low, Close, MA1, MA2, Signal
thanks
Hi,
I'm using backtraders ATR. It doesn't seem like I'm getting the same ATR values as in metatrader. I have downloaded metatraders data and noticed backtrader's ATR values are different than in metatrader when comparing.
Additionally, I'm looking for the original welles wilder version (non smoothed). on Github, it looks like an SMA was used so I thought it'd be the same as in metatrader.
Anyone who has the original version by any chance?
thanks
@run-out Perfect! you always come to the rescue :) do you then also know how to refer to the datafeeds in the init / next functions?
I have now created the three timeframes as follows which seems to work. When I log, I'm getting the closes of the 2 minute timeframe. Can't see how to refer to the other two though.
# Add a strategy
cerebro.addstrategy(resampling)
# Create a Data Feed
minute_data = bt.feeds.PandasData(dataname=df2020)
two_minute = cerebro.resampledata(minute_data, timeframe=bt.TimeFrame.Minutes, compression=2)
five_minute = cerebro.resampledata(minute_data, timeframe=bt.TimeFrame.Minutes, compression=5)
ten_minute = cerebro.resampledata(minute_data, timeframe=bt.TimeFrame.Minutes, compression=10)
@run-out thanks a lot, really appreciated! hadn't read that far yet so should have just read the full guide first.
@dasch Yes. I realized that because the lowest dataframe is 2 minutes, there will never be a time ending on 5. I tried the following work around where I'm separately adding the one minute frame
# Add a strategy
cerebro.addstrategy(resampling)
# Create a Data Feed
data = bt.feeds.PandasData(dataname=df2020)
one_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=1)
two_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=2)
five_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=5)
ten_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=10)
when logging the 5-minute closes I can see now it works properly
2020-01-02 09:00, 1.12075
2020-01-02 09:01, 1.12075
2020-01-02 09:02, 1.12075
2020-01-02 09:03, 1.12075
2020-01-02 09:04, 1.12075
2020-01-02 09:05, 1.12087
2020-01-02 09:06, 1.12087
2020-01-02 09:07, 1.12087
2020-01-02 09:08, 1.12087
2020-01-02 09:09, 1.12087
2020-01-02 09:10, 1.12086
2020-01-02 09:11, 1.12086
2020-01-02 09:12, 1.12086
2020-01-02 09:13, 1.12086
2020-01-02 09:14, 1.12086
2020-01-02 09:15, 1.1207799999999999
thanks for the help guys
I'm also interested in contributing. I still have lots to learn about backtrader itself but I'm learning as I'm going and I have some ideas to implement. What's the update on this?
@ab_trader thanks!! that seems to work.
@run-out To have a channel to chat. I'm going off @Atul-Patel's message where he said he created a discord group so I was wondering if that is still going.
I'm trying to resample from 1 minute to 2, 5 and 10 minutes. The only problem I'm having is when resampling, the first OHLC data I'm logging of the 2,5 and 10 minute is exactly the same as the first 1 minute OHLC data. after that it resamples properly, however it then is out of sync.
an example will make it more clear when sampling 1 minute to 2 minute data:
Output in the log:
Starting Portfolio Value: 1000000.00
2020-08-12 00:00, O: 1.17383, H: 1.17391, L: 1.17372, C: 1.17391
2020-08-12 00:02, O: 1.17391, H: 1.17408, L: 1.17384, C: 1.17384
2020-08-12 00:04, O: 1.17384, H: 1.17384, L: 1.17377, C: 1.17377
2020-08-12 00:06, O: 1.17377, H: 1.17389, L: 1.17376, C: 1.17386
dataframe info:
Open High Low Close Volume
Datetime
2020-08-12 00:00:00 1.17383 1.17391 1.17372 1.17391 23
2020-08-12 00:01:00 1.17391 1.17408 1.17390 1.17390 18
2020-08-12 00:02:00 1.17390 1.17390 1.17384 1.17384 33
2020-08-12 00:03:00 1.17384 1.17384 1.17378 1.17378 22
2020-08-12 00:04:00 1.17378 1.17378 1.17377 1.17377 25
2020-08-12 00:05:00 1.17377 1.17382 1.17376 1.17382 39
2020-08-12 00:06:00 1.17382 1.17389 1.17382 1.17386 36
The first candle should be O:1.7383 H:1.17408 L:1.17372 C: 1.17390 but for some reason it always takes over the very first minute candle which causes all the rest of the candles to be out of sync.
my code below:
class Resampling_test(bt.Strategy):
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):
pass
def next(self):
self.log('O: %.5f, H: %.5f, L: %.5f, C: %.5f' %(self.datas[0].open[0], self.datas[0].high[0], self.datas[0].low[0], self.datas[0].close[0]))
if __name__ == '__main__':
cerebro = bt.Cerebro()
# Add a strategy
cerebro.addstrategy(Resampling_test)
# Create a Data Feed
data = bt.feeds.PandasData(dataname=df2020)
two_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=2)
# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
many thanks
@run-out me neither but it could be a start and stimulate people to work together if there's a direct channel of communication. I haven't worked on anything open source related and I just want to learn more and help improve this project.
@run-out me neither but it could be a start and stimulate people to work together if there's a direct channel of communication. I haven't worked on anything open source related and I just want to learn more and help improve this project.
@run-out To have a channel to chat. I'm going off @Atul-Patel's message where he said he created a discord group so I was wondering if that is still going.
Is there a way of realtime communication created like discord? I think that would be useful.
I'm also interested in contributing. I still have lots to learn about backtrader itself but I'm learning as I'm going and I have some ideas to implement. What's the update on this?
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 would but I can't see how to add an attachment? if not possible, I'll add it to dropbox and then send it that way
@dasch much appreciate the quick response. I've tried it but it doesn't work. I haven't found any posts on the forum where it was mentioned either unfortunately.
for simple MA crossover strategy, when an order is created, if the next bar triggers the entry but simultaneously hits the target, it will only execute the entry and then exit the bar after that on the open. I can't figure it out. I've been trying different order types but I haven't been able to change the behavior. I've experimented with cheat on open but that didn't get me anywhere
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)
# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
log for reference. it should both execute the buy and sell order 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: 1, Comm 0.00
2020-08-12 06:30, SELL EXECUTED, Price: 1.17203, Cost: 1, Comm 0.00
2020-08-12 06:30, Order Canceled/Margin/Rejected
2020-08-12 06:30, OPERATION PROFIT, GROSS 0.00018, NET 0.00018
@dasch I just read the full thread. this seems to be an outstanding issue for a while. I hope it'll get fixed at some time. I really like the library and I want to use it for livetrading but I hope this problem doesn't jeopardize it. what do you now use for livetrading?
@dasch thanks for your response. yes as described in my previous post, I have used boundoff which fixes the bar issue. when I use rightedge=True or any of the other parameters. it doesn't fix my timebar issue however