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
@ab_trader thanks!! that seems to work.
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
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