The best way to extract data from your backtest is Analyzers.

You can use built in analyzers or as in your case, build a custom analyzer to track the data during each iteration of the back tests.

At the end, you will usually end up with a dictionary (if you build it that way) out of which you can build your dataframe.

@songyi-gao https://community.backtrader.com/topic/1048/using-cheat-on-open-and-cheat-on-close-together/2

Bildschirmfoto 2021-08-30 um 10.09.07.png

@dindom999 You may try to track the memory consumption. Also it could be a problem with your code - but without seeing it, it is hard to tell.

Probably the following posts could be relevant:

https://community.backtrader.com/topic/2397/high-memory-consumption-while-optimizing-using-influxdb-data-feed
https://community.backtrader.com/topic/3552/multicore-optimization-cause-performance-degradation
https://community.backtrader.com/topic/2593/adding-influxdb-datafeeds

@andi

simply use datas[1] for monthly sma.

sma_monthly = bt.SimpleMovingAverage(self.datas[1].close)

@vladisld
Thanks for your advice and I have now finished writing and testing my code, it can work really well now.

But my last step is try to plot the performance. I tried to use the basic plot function, but it seems that it plot the stocks separately (as shown in the portfolio). Is there any way to plot at portfolio value?

Thank you in advance.

Screenshot 2021-08-09 221156.jpg

@run-out
Thanks for the detailed reply. Agree there was some clumsiness about the setup, but I had mirrored what I had in a single data example which was working. I have streamlined it now though per your suggestion.
Anyway, after some banging of my head on the desk, I found what was wrong with my multi-data version and it was simple.....the magical runonce=False, which i hadnt copied over from my single-data example.

# Run over everything cerebro.run(runonce=False, maxcpus=1) # runonce = False is required

now it all works as expected. Thanks for helping me though it. Hopefully the Dynamic Trailstop indicator is useful to other folks too now that its shared. Cheers!

@run-out I understand that - I mentioned that in the initial post. My question is why were close_over_sma, close_over_ema, sma_ema_diff and buy_sig created in the Strategy rather than one or all of them being created as their own Indicator object?
What benefit was achived by creating them in the Strategy, and what benefit would have been achieved by creating them as Indicators?

The question isn't about init vs next. I'm trying to understand when I should create my own Indicator objects and when I should just put everything into the Strategy object.

@trepx86 Have a look at my answer here

@paulchui What have you tried so far?

@bo Another option is to utilize the prenext method. See the example here:
https://www.backtrader.com/blog/2019-05-20-momentum-strategy/momentum-strategy/#next-and-prenext

DUPLICATE POST https://community.backtrader.com/post/17875
@newtrader15 Please do not post the same question twice.

Please redirect to here

https://community.backtrader.com/post/17875

Start date: 01.01.2019
End date: 01.06.2021

Result for 30m and 1h timeframes:
Total trades: 2

every time pre_load consume time :17.86236882209778 2019-01-10, BUY EXECUTED, Price: 3819.86, Cost: 10000.00, Comm 10.00 2019-01-10, SELL EXECUTED, Price: 3726.32, Cost: 10000.00, Comm 9.76 #######2019-01-10 BTCUSDTTF2 price 3819.86 Closed: PnL Gross -244.87, Net -264.63####### 2019-01-20, BUY EXECUTED, Price: 3590.40, Cost: 9973.54, Comm 9.97 2019-01-28, SELL EXECUTED, Price: 3479.01, Cost: 9973.54, Comm 9.66 #######2019-01-28 BTCUSDTTF2 price 3590.4 Closed: PnL Gross -309.42, Net -329.06####### Profit Percent: 10 Stop-loss Percent: 5 Final PnL: -593.69

@coder1111 Can you share your custom analyzer ?