Hi @vladisld , @run-out , thanks for your answers, I'm still quite confused by compression, I never met this concept in any papers, is there any doc describing it intuitively? I've read its source code at https://github.com/mementum/backtrader/blob/master/backtrader/analyzer.py#L399-L406: # Apply compression to update point position (comp 5 -> 200 // 5) point = point // self.compression # Move to next boundary point += 1 # Restore point to the timeframe units by de-applying compression point *= self.compression What's the purpose of the above code?

@ab_trader said in Basic MultiTimeframe order: @Paul-Park said in Basic MultiTimeframe order: So nextstart() ensures that the higher time frame completes the bar before letting the program continue? nextstart() has no relation to time frames. Ahh I see where my confusion was now. Thank you very much.

@André-Tavares Sorry, misread the question.

I can open an account from Brazil with them, but cannot trade brazilian assets on the Bovespa Exchange.

I managed it to pass the error message with the symbol: I just declared the symbol like this: w, h = 2, len(sheet.index) symbols = [[0 for x in range(w)] for y in range(h)] The code is running now, but I think it stops anywhere, because if I plot the equity it just plotts it ones and than nothing happens and the code don't stop running. What do you think about the 3 functions? Do you see something what is wrong?

I've made a few changes to your code. Thanks for posting like that. In my code below, startdate would more likely be an input parameter but I left it like this for the illustration. You may wish to add an exception if startlength is None after the start date, just in case. from datetime import date def __init__(self): self.start_length = None # Your other stuff here. def next(self): startdate = date(2012, 1, 4) # This would probably actually be an input parameter. date = self.datas[0].datetime.date() if date < startdate: return elif date == startdate: self.start_length = len(self) else: if self.start_length is None: raise ValueError("Error: start_length not properly set.") # Find Range num_bars = len(self) - start_length Dayhigh = max(self.datahigh.get(size=num_bars, ago=0)) Daylow = min(self.datalow.get(size=num_bars, ago=0)) Range = (Dayhigh - Daylow) print(date, Dayhigh, Daylow, Range)

@run-out I mean there is no error message. My algorithm seems to always underperform in MACD.

The 'lines' are typically whatever you put into your strategy. The starting point would be your trading data, OHLCV open interest. This of course would have a datetime element. But you could also add custom information or signal lines to your trading data using a custom data class and these custom data lines would also show up in your strategy. And then also you could use indicators in your strategies which have lines defined as part of the indicator or defined by you in a custom indicator.

@Quanliang-Xie said in Passing data into data feed one by one: I want to test a single strategy using a series of csv files from a folder There are several scenarios: Running the same strategy on each csv file separately ( separate broker, account balance ) and sequentially (one after another): In this case, just put the cerebro creating code inside your for loop. In the code above the same cerebro instance is used to host all the datas and strategies. Since the datas are hosted directly in cerebro instance and not in strategy - all the added datas are just accumulating in the same cerebro instance. Same as above, only now run all the strategies simultaneously Basically very similar - just put the code under for loop inside a separate function which will recieve the csv path as a parameter and try to use the 'multiprocessing' python capabilities to run it. Alternatively, you may try to use the Backtrader optstrategy as @run-out has suggested, however, this is more involved and wasn't designed for your particular use case. Running all the csv files against the same broker account (sharing the account cash) In this case you just need to add all the datas to the same cerebro instance as you are doing currently. However, only a single strategy needs to be added to the cerebro instance. In addition the cerebro instance should be run only once as well - and not under for loop.

Got it. I misunderstood something stupidly.

I am keen to see responses on this too. For Stop Losses you can place these with your broker at the time of placing the order. The SL will be hit and executed by the broker regardless of Backtrader timeframes. I typically work on 1min bars in the current market however fast price movements sometimes mean I am not getting the best close position timing when the exit condition is hit. The only solution I've been able to think of (but not yet tried) is to set up 'data' and 'data1' on two different timeframes. 'data' would be for say 5 sec bar (for closing positions) and 'data1' would be for the entry conditions on a higher timeframe (i.e. 1min).

Thank you so much run-out. This works!! I need sometime to review the documentation to fully understand but thank you so much !

Thank you so much! That solved my problem. To thoes who has the same problem, remember also to improt timeframe from backtrader!

Great, yeah that's pretty much what I was trying to do. Do you happen to have a way of saving settings too? For example the default chart plots a 'line' for the ohlc data and I went into scheme.py to change it to 'candle' and the way I usually update the whole albacka_backtrader_api is I just go on github and download the zip and replace the old one, so I lose settings like that. Is there a way to save all that or not update those files?

To those that may come across this thread, I cannot explain why the issue is occurring, but if you pass a name to the default data when utilizing 'adddata', the legend will look normal again. Fixed #Don't use this: cerebro.adddata(data) #Use a name with the data: cerebro.adddata(data, name='OHLCV_jt') The name comes across in the heading / legend of the master Bokeh plot as so:

@run-out https://stackoverflow.com/questions/59003693/understanding-converting-thinkscripts-compoundvalue-function i need to convert this in backtrader and want to calculate ha_open like this

when using multiple data sources, you will get notified of every change. when resampling, if data advances, on replay if data changes (in that case, data will not necessary advance). So to know if the data source advanced, you need to check the length of data. example: if self._last_len > len(self.datas[1]): self.log(self.datas[1].close[0]) self._last_len = len(self.datas[1]

@run-out Sorry I didn't mean to put in that top block of code... wish we could edit.