@zuj you should self.buy to long a stock and use self.sell to short another stock

@ab_trader Your solution is very good, thank you.

@ab_trader Thank you.

What I mean is get datetime in indicator once function.

I figure out a solution, which is pass strategy.datas[0].datetime as a data, so I can access the date by bt.num2date(self.datas[1][i])

I don't know if it is a good one, but it works

Regards

@avys Thanks for reporting it. Please open an issue in the backtrader2 repo (https://github.com/backtrader2/backtrader/issues). It would be great if the following info could be provided:

Link to the community discussion (this page) More technical description of the error in the existing code, possibly including the problematic code location if you have one. Example of the correct vs error calculation including the data set used for both If possible, a short test that could be used for reproducing the error.

( example issue: https://github.com/backtrader2/backtrader/issues/41 )

@weibudda

as a guess - indicators are recognized and initialized within the strategy class, but not some object. therefore it is possible that all line written in the __init__ above are meaningless from the bt point of view.

@balibou did you figure a solution for the above. I am fairly new to python and was working to implement the idea discussed by you.

@Yacc-Don @Yacc-Don Or you are testing if it is Nan. Is it equivalent to math.isnan()?

@Yacc-Don Or you are testing if it is Nan. Is it equivalent to math.isnan()?

The reason you are getting the discprency is the nature of how ATR is calculated. ATR has the following definition:

The range of a day's trading is simply [high − low]. The true range extends it to yesterday's closing price if it was outside of today's range.

Note that ATR must have the ability to look back one period. This one period look back requirement means that all ATR calculations will need n+1 periods for warmup calculation.

You can check this yourself by putting say bt.ind.SMA by itself for n periods (5 in this case):

2015-07-08, Close: 30.64, sma: 31.37, 2015-07-09, Close: 30.02, sma: 31.04,

Now add in the ATR with the same period, and you will see the results start one period later.

2015-07-09, Close: 30.02, sma: 31.04, vol: 0.64 2015-07-10, Close: 30.82, sma: 30.88, vol: 0.70

None of this has anything to do with your function, but is a matter of how ATR is calculated.

thanks. i will try ...

please advice if this can be done or a zipline cane achieve this?

@run-out @rajanprabu

Thank you very much! I got it fixed, I just changed:
the logging function from

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

to

def log(self, txt, dt=None): ''' Logging function for this strategy''' dt = dt or self.datas[0].datetime.datetime(0) print('%s, %s' % (dt.isoformat(), txt))

@J-Javier-Gálvez Thanks. Your solution helped.

Thanks for looking in to it. Very much appreciate it. I hope it was useful.

Interesting but this indicator must be used with the Elliot wave method, the Fibonacci retracements method or the projected retracements method to constitute an efficient trading method.

You will have to code that in manually yourself. After tax investing is not in the Backtrader mandate. Good luck.

@Mariano-Volpedo

Great strategy! Tried to replace with moving average and more on __init__ instead of next.
The results swift to 60-63 instead of ~55. Not sure is it because of any calculation error....

def __init__(self): self.l.m = bt.ind.MovAv.Simple(self.data.close, period=self.p.period) #replace with median self.l.nl=bt.And(self.data.close>self.l.m,self.data.close>self.data.close(-1)) self.l.nh=bt.And(self.data.close<self.l.m,self.data.close<self.data.close(-1)) self.l.upSum = bt.ind.SumN(self.l.nl, period=self.p.period) self.l.downSum = bt.ind.SumN(self.l.nh, period=self.p.period) self.l.mmi= 100.0 * (self.l.upSum+self.l.downSum)/(self.p.period - 1)