@greenleafone7 Not really sure about it but it seems this parameter is provided for any inherited implementation of CommInfoBase to use.

I figured out with eclipse by configuring with python and i am able to run all python test from the project backtrader-master.
Just to need see how python works.
We can close this thread.
Thank you

iirc it should be enough if you first load the company with the earliest start date. It was long time ago, but I didn't do any special work with the index to backtest thru multiple tickers.

@crazy25000 i'll look into it thanks

@fredyellow said in progress bar / ETA during optimization:

@crazy25000 said in progress bar / ETA during optimization:

Just finished implementing tqdm for optimizations. The status bars are inline and stay at the top. This way I can view the ETAs and overview of the opt runs:

2a687536-3cad-4ad7-ac5a-eeec27394531-image.png

Excellent!

Do you have a minimal code example?

Here's a minimal code example in Jupyterlab Notebook:

from datetime import datetime import backtrader as bt from tqdm.auto import tqdm pbar = tqdm(desc='Opt runs', leave=True, position=1, unit='run', colour='violet') class OptimizeStrategy(bt.Strategy): params = ( ('p1', 9), ('p2', 21), ) def __init__(self): self.ema1 = bt.talib.EMA(self.data, timeperiod=self.p.p1, plotname='EMA1') self.ema2 = bt.talib.EMA(self.data, timeperiod=self.p.p2, plotname='EMA2') self.crossover = bt.indicators.CrossOver(self.ema1, self.ema2) def next(self): if self.crossover > 0: if self.position: self.close() self.buy() elif self.crossover < 0: if self.position: self.close() self.sell() def bt_opt_callback(cb): pbar.update() def runstrat(): cerebro = bt.Cerebro(maxcpus=1) cerebro.optstrategy(OptimizeStrategy, p1=range(5, 20, 5), p2=range(50, 200, 10)) data = bt.feeds.YahooFinanceData(dataname='AAPL', fromdate=datetime(2016, 1, 1), todate=datetime(2017, 1, 1)) cerebro.adddata(data) cerebro.optcallback(cb=bt_opt_callback) stratruns = cerebro.run() if __name__ == '__main__': runstrat() print("Done")

1fa04115-1cbb-483e-9196-6f73c55f2016-image.png

@ab_trader Thanks, anyone recommend?

@ab_trader: I have looked into my data and while I am supposed to only have tickers traded on the NYSE in my feed, 5 of them were actually traded on European and Asian markets, following a slightly different calendar for holidays. Removing them solved the problem rergarding the two calls of next on 24-03-2016, and my holdings are now very closely aligned in Zipline and Backtrader every days! thanks for the help.

I still have some discrepancies in the returns, apparently caused by uneven weighting of my positions in Backtrader, which should follow a simple 1/N weighting scheme. I have not had time to look into this yet, and it is not even related to my orginal question. But if there is something odd you spot in my code, pls let me know.

@petehe said in question about sample code mixing-timeframes:

it can't work out

should be I can't work out

@run-out He, well I am very well aware that using official indicators is not a good move usually, just because too many would already be using it. This is why I too have built my past strategies on custom tailored indication and always shun away from all these "easy" make rich scheme indicators, especially RSI with its "buy 30 sell 70 be rich" lazy and untrue success formula that I see repeated everywhere.

I am still not doing that however, but I seek to automate normalization, for which I have observed RSI is a pretty good candidate. This recent boom in BTC has caused proven strategies to be thrown out of the window, simply because interval-volume has increased more than tenfold in just a year, and thus also the turbulence has increased. I managed to devise a pretty promising strategy for the range of 1.1.21 to end of February, but the problem is, it doesn't scale back to last year at all, while of course the old strategies don't apply to this new craze.

I have since though about a machine learning learned scaler variable plan, but it is elaborate and takes too much time to implement for now. Since the market is in motion at this very moment, I simply try to find a heuristic scaling solution, and by observing the Binance RSI with its snuggle effect around price trends independent of their actual value, I just want to fish this out in order to normalize my strategy for the broader activity-scale spectrum. Ambitious perhaps, but I will see if it is really any better than my current work.

So be reassured that I wont do some simplistic buy/sell-margin foolishness here. ;)

Also, the workings of the Binance RSI(6) indicator are decrypted, and there are no shenanigans in the calculation other than that it is difficult to follow up on how the implementation would work. I doubt they would ever just change that, but even if, the fear that any strategy would collapse because of that change is unfounded I think, since I don't extract their indicator, but replicated it. So if whatever I do with it works out, I will just keep it no matter what Binance does later on.
Now what they do with RSI(12) and RSI(24) is still a mystery, but if knew, I reckon it would play out the same.

@lucpc Seems like there are NA values in the Date column, I'm fixing that now

Hi,
I'm quite new to BackTrader and it's fantastic. I'm new to python in general...
I ran into the same problem I think and here is how I tried to run multiple strategies on multiple stocks (csv files).

import backtrader import datetime import os import matplotlib.pyplot as plt import numpy as np import pandas as pd from Strategies.GoldenCross import GoldenCross from Strategies.BuyHold import BuyHold from Strategies.TestStrategy import TestStrategy path_dir = r'C:\__xxxxxx' #directory path_dir_strats = r'C:\__xxxxx' # directory with strategies (not used here) a = 0 for filename in os.listdir(path_dir): if filename.endswith(".csv"): a = a+1 # Create a Data Feed data = backtrader.feeds.YahooFinanceCSVData( dataname=filename, # Do not pass values before this date fromdate=datetime.datetime(2017, 1, 1), # Do not pass values after this date todate=datetime.datetime(2020, 12, 31), reverse=False) #---------------------------------------------------------------------------------------------- cerebro = backtrader.Cerebro() cerebro.adddata(data) cerebro.broker.setcash(1000000) cerebro.addstrategy(GoldenCross) cerebro.addsizer(backtrader.sizers.FixedSize, stake=1000) # Set the commission - 0.1% ... divide by 100 to remove the % cerebro.broker.setcommission(commission=0.01) print('Reference stock:', filename) print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) cerebro.run() print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) print('') nomefilenoext = os.path.splitext(filename)[0] nomefinale = nomefilenoext + "_GoldenCross" salvafigura = os.path.join(path_dir, nomefinale) #per stampa, se il parametro è 0 non stampa i grafici ma salva solo le figure cerebro.plot(file_path=salvafigura, stampa=0) #---------------------------------------------------------------------------------------------- #---------------------------------------------------------------------------------------------- cerebro = backtrader.Cerebro() cerebro.adddata(data) cerebro.broker.setcash(1000000) cerebro.addstrategy(TestStrategy) cerebro.addsizer(backtrader.sizers.FixedSize, stake=1000) # Set the commission - 0.1% ... divide by 100 to remove the % cerebro.broker.setcommission(commission=0.01) print('Reference stock:', filename) print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) cerebro.run() print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) print('') nomefilenoext = os.path.splitext(filename)[0] nomefinale = nomefilenoext + "_TestStrategy" salvafigura = os.path.join(path_dir, nomefinale) #per stampa, se il parametro è 0 non stampa i grafici ma salva solo le figure cerebro.plot(file_path=salvafigura, stampa=0) #----------------------------------------------------------------------------------------------

The part between the ------- lines is what I repeat for each strategy.
I put every csv file in a certain folder.
I've modified just a little the plot function in order to save the picture and to print or not the graph.

I tried to use a for cycle for each strategy, in the defined folder, but I did not suceed on passing the right name to the strategy because the cerebro.addstrategy() need a class name, not a string (any suggestion?).

Thank you.

@xue said in Such problems meeted!:

self.sma = bt.indicators.MovingAverageSimple(self.datas[0],period=self.params.maperiod)

Try:

self.sma = bt.indicators.MovingAverageSimple(period=self.params.maperiod)

Sorry! the last error is not about python, it is a spell error

self.log(...)

is correct.
'''
set.lot(...)

is not correct. thanks for you patient answer.

@ololo Im new here and perhaps not much help, but from the Orders-General page in the docs:
Member Attributes:

ref: unique order identifier

created: OrderData holding creation data

executed: OrderData holding execution data

so you can reference the order.exectuted attribute and compare with the data[0]'s which is current price of feed in handled in the strategy logic I believe.

Hey thanks. Naturally, we can just chalk this up to me being dumb. I apparently did fill my database with individually cast str() for some wild reason in the beginning. Not sure why I had to get hung up here for a day to figure it out, but seeing it finally load just now after re-doing the database just now was damn sweet. Thanks again.
code-snapshot1.png

(The silly error, commented out and pasted above. Cheers)

@dasch said in Bokeh indicator lines dont show:

produce the custom indicator line. but if it

Thanks Dasch.. I have opened a new issue https://github.com/happydasch/btplotting/issues/13

One more update.. I tried drawing horizontal lines.. They work perfectly.. Really weird.. I am not able to debug :(btplotting_horizontal_lines.PNG

All I am trying to do is plot the zigzag indicator that the admin of backtrader coded here https://community.backtrader.com/topic/773/zigzag-indicator

@bnewell I just tested this talib function on just under two months of minute data, and the times are almost the same.

10 cyles: The average time for ta_lib = True is 1.361 The average time for ta_lib = False is 1.313

I can't reproduce the problem you are having, you may have to troubleshoot on your end.