@run-out @ab_trader
I see.
I understood bt's approach to ordering.

I really appreciate all of you.
And thank you so much for your efforts to understand my poor English.

@aqa20 said in Different results with resample data and add data methods!:

@emr

Do you know if this compression is the same as when done by backtrader (ie bar2edge, boundoff, rightedge etc?

I believe so

I noticed that you can have very different presentation of 5mn, 1h etc data depending of the data provider. For me, it was differences between data from MT5 & data resampled by BT. For example, 1h data from MT5 had a different close value. You may want to check the M5 & H1 open & close values to find if it is the one of neighboring minutes and also check the doc to find if some additional parameters (boundoff, rightedge etc.) can bring you the results you want

Also, I noticed during my tests that if some minutes are missing, the resampling to for ex. H8 may lead to errors (closure of the bar occur later than expected - I still have to find the time to log an issue in BT2 for that)

@backtrader I've looked on it, and I am going to use it as a baseline for dd length observer.

One of the latest additions lets you do direct time comparisons directly to lines to generate signals. Probably nobody has used it yet. An example:

class MySignal(bt.Indicator): lines = ('mysignal',) def __init__(self): self.lines.mysignal = self.data.datetime > datetime.time(10, 30)

This generates an indicator which can be used as a signal to only execute orders when the daily time goes over 10:30.

But since you are probably looking for day, you'll need to work it out in the next method comparing the self.data.datetime.date() (maybe even getting the weekday) against something of your choosing

@ab_trader true. anyway it's not what I'm looking for as commission is not included into calculation.

You can use it without being merged. Again, see: Community - EoDevelopment 1.x

@ab_trader - I am doing my best. I have already submitted pull requests for new Fisher Transform indicator and Simulated Order. And I am sharing all my code snippets here along with explanations whenever relevant.

When I say the framework should have this or that, I dont mean that someone should implement them but that we shall implement it for everybody's benefit.

@ab_trader DRo = Daniel Rodriguez for those that didn't immediately get, it took me a few secs :)

@bernardlin
I have something critical to point out.

Backtesting forex pairs trading has a major flaw. It uses a different way to calculate pnl of the backtest because the assets involved rarely have the same quote or base currencies.

The only exception to this is if the assets involved have the same base currency, e.g USDCHF USDJPY. If this pair appear to be cointegrated, then the returns of the backtest would be the same as calculating pnl of, say, GLD GDX.

But if the forex assets involved are of the same quote currency or of completely different currency bases and quotes, then the calculation of the pnl is completely different.

If one proceeds and backtest these cointegrated pairs the same way one do regularly then one would get the wrong result.

I am really keen to know how you went about backtesting cointegrated forex pairs and getting the correct result using Backtrader. I am yet to do that.

Hi,

i do like this, as suggested by @backtrader: I preprocess all my securities data including as an extra column their membership status. I do this while creating the survivorship bias free dataset.

In 'next' I look for it as it is another indicator. If True I trigger a EW target buy order otherwise a 0% target sell order.

@Laurent-Michelizza Thank you very much! when I log the position,I also find this question and use almost your way to solve it.
But in the future,I guess,we do a auto-close function when the future expires, it is more easy to use. After this four times reading the source code,I maybe try this function.

@ab_trader If I can use the fractal indicator to reference the true/false for any candle, like fractal[-14] to find out if 14 candles back was a high or low, then it will work, because I have to be able to get the high/low value from the fractal, not just knowing whether or not it is. I'll mess around with it, definitely looks cleaner than my method lol.

@vladisld said in Rollover multiple contracts [help needed]:

@chewbacca said in Rollover multiple contracts [help needed]:

File "/home/user/PycharmProjects/backtrader/Strategies/VixLive.py", line 615, in notify_timer
self.initial_position = self.position.size
File "/home/user/PycharmProjects/backtrader/venv/lib/python3.8/site-packages/backtrader/lineseries.py", line 461, in _ _ getattr _ _
return getattr(self.lines, name)
AttributeError: 'Lines_LineSeries_LineIterator_DataAccessor_Strateg' object has no attribute 'position'

The error backtrace above seems strange. Accessing the position property in the strategy should call the bt.Strategy's getposition method:

class Strategy: ... def getposition(self, data=None, broker=None): data = data if data is not None else self.datas[0] broker = broker or self.broker return broker.getposition(data) position = property(getposition)

This should be reflected in the error backtrace. It looks like the self.position was called from the indicator and not from the strategy.

It could be useful to if you could share the whole VixLive.py code?

By default data0 is used as the "primary", correct?
vx2_1_min = cerebro.rolloverdata(*rollfeeds_vx2_minute, **rollkwargs_vx2_minute) -- is data0 since it's called & added first.

Correct me if I'm wrong..

@run-out

Thanks again for the long reply!
I just tried cheat on open, but the result is the same.
I thought about including a buy margin and it seems this is the way to go... for that example...
Hence, i assume the orders are not done by theirs reference numbers otherwise order 75 would not be canceled?

Best

@amit Have a look here for highest and lowest.

@ssbilis No because were are dealing with the results of get which is a list. You want the last item in the list, which is -1

Hello @samk

This strategy might have some flaws but it shows quite well the intention to buy when the price is in bullish trend...

How would you change it to fit more your ideas ?

perfect, so this is it:

class CustomDataLoader(btfeeds.PandasData): lines = ('TOTAL_SCORE','Beta',) params = ( ('openinterest',None), #None= column not present ('TOTAL_SCORE',-1), ('Beta',-1) ) datafields = btfeeds.PandasData.datafields + (['TOTAL_SCORE','Beta'])

@RandyT said in Pyramiding support:
Thanks Randy for getting back.

I do this as follows:
class MyStrategy(bt.Strategy):
params = (('short', 5), ('long', 10))
def init(self):
self.inds = dict()
for i, d in enumerate(self.datas):
self.inds[d] = dict()
self.inds[d]['sma_s'] = bt.indicators.MovingAverageSimple(d.close, period=self.params.short)
self.inds[d]['sma_l'] = bt.indicators.MovingAverageSimple(d.close, period=self.params.long)
self.inds[d]['start_time'] = d.datetime.date(self.params.long)
self.inds[d]['start_flag'] = 0

def prenext(self):
for i in range(3):
if self.datas[i].datetime.date() == self.inds[self.datas[i]]['start_time']:
self.inds[self.datas[i]]['start_flag'] = 1
log_str = log_str + 'i={}, date={}, sma_s={}, sma_l={}\n'.format(i, self.datas[i].datetime.date(),
self.inds[self.datas[i]]['sma_s'][0],
self.inds[self.datas[i]]['sma_l'][0])
elif self.inds[self.datas[i]]['start_flag'] == 1:
log_str = log_str + 'i={}, date={}, sma_s={}, sma_l={}\n'.format(i, self.datas[i].datetime.date(),
self.inds[self.datas[i]]['sma_s'][0],
self.inds[self.datas[i]]['sma_l'][0])

prenext() process data when time is not the same. If the time is the same, then go to next().