@vladisld Thank you for your reply.

Is this the correct way to do it?

from backtrader.feeds import GenericCSVData

class DataCSV(bt.feeds.GenericCSVData):
    
    lines = ('ratio', )
    
    params = (
        ('dtformat', '%d/%m/%Y'),
        ('datetime', 0),
        ('time', -1),
        ('open', 4),
        ('high', -1),
        ('low', -1),
        ('close', 1),
        ('volume', 2),
        ('openinterest', -1),
        ('ratio', 3),
    )

Note: It now says ('open', 4) because I added open values because I keep getting NaN as portfolio value. I just noticed that backtrader buys at open and sells at close.

Hello and thank you for your time.

I'm currently trying to apply a single strategy (buy and sell with a signal of a ratio value) to mutltiple csv (each csv have info from different tickers).

This was made following the examples in:

https://backtest-rookies.com/2017/08/22/backtrader-multiple-data-feeds-indicators/

https://www.backtrader.com/docu/extending-a-datafeed/

All the test files look the same:

date,close,volume,ratio
31/01/2000,10,50,0.2
29/02/2000,20,100,0.2
31/03/2000,30,150,0.2
28/04/2000,40,200,0.5

I'm getting a data error as it does not recognize the format inside the params.

ValueError: time data '31/01/2000' does not match format '%Y-%m-%d %H:%M:%S'

Here is the complete code, I will gladly appreciate your help in order to make it work.

import backtrader as bt
from datetime import datetime

class hopeitworks(bt.Strategy):
    def __init__(self):
        self.inds = dict()
        for i, d in enumerate(self.datas):
            self.inds[d] = dict()
            self.inds[d]['ratio'] = d.ratio


    def next(self):
        for i, d in enumerate(self.datas):
            dt, dn = self.datetime.date(), d._name
            pos = self.getposition(d).size
            if not pos:  
                if self.inds[d]['ratio'][0] <= .2 and self.inds[d]['ratio'][0] > 0:
                    self.buy(data=d, size=1)
            else:
                if self.inds[d]['ratio'][0] >= .5:
                    self.sell(data=d, size=1)

#Variable for our starting cash
startcash = 10000

#Create an instance of cerebro 
cerebro = bt.Cerebro()
 
#Add our strategy
cerebro.addstrategy(hopeitworks)

class DataCSV(bt.feeds.GenericCSVData):
    params = (
        ('dtformat', '%d/%m/%Y'),
        ('datetime', 0),
        ('time', -1),
        ('open', -1),
        ('high', -1),
        ('low', -1),
        ('close', 1),
        ('volume', 2),
        ('openinterest', -1),
        ('ratio', 3),
    )
    
from backtrader.feeds import GenericCSVData

class DataCSV(GenericCSVData):

    # Add a line to the inherited ones from the base class
    lines = ('ratio',)

    # openinterest in GenericCSVData has index 7 ... add 1
    # add the parameter to the parameters inherited from the base class
    params = (
            ('ratio', 8),    
    )

#create our data list
datalist = [
    ('data/aaadata.csv', 'TICKERAAA'), #[0] = Data file, [1] = Data name
    ('data/bbbdata.csv', 'TICKERBBB'),
    ('data/cccdata.csv', 'TICKERCCC'),
]


#Loop through the list adding to cerebro.
for i in range(len(datalist)):
    data = DataCSV(dataname=datalist[i][0])
    cerebro.adddata(data, name=datalist[i][1])

# Set our desired cash start
cerebro.broker.setcash(startcash)

#Run Cerebro Engine
cerebro.run()


# #Get final portfolio Value
portvalue = cerebro.broker.getvalue()
pnl = portvalue - startcash

# #Print out the final result
print('Final Portfolio Value: ${}'.format(portvalue))
print('P/L: ${}'.format(pnl))

#Finally plot the end results
cerebro.plot()

@davidavr Thank you for your insight.

As I understand your response:

In excel i have

         A              B          C          D
1               ticker1               ticker 2
2           close   rev       close     rev
3 date1
4 date2

and my csv should be

DATE, TICKER, CLOSE, REV
date1, ticker1, close, rev
date2, ticker1, close, rev
.
.
.

date1, ticker2, close, rev
date2, ticker2, close, rev

then in the example code I should add just the rev like this?

df = pd.read_csv(filename, parse_dates=['date'])
for tkr, grp in df.groupby('ticker'):
    data = bt.feeds.PandasData(
        dataname=grp,
        datetime='date', close='close', rev='rev',
        open=None, high=None, low=None, volume=None, openinterest=None,
        plot=False,
    )
    cerebro.adddata(data, name=tkr)

and the strategy can be as simple as this???

def next (self):
       if not self.position:
          if self.rev <30:
              self.buy(size=1)
       else:
            if self.rev >50:
                self.sell(size=1)

Sry if I did not get that right.

Hi, I'm fairly new to backtrader and python in general; and as I'm reading the documentation and some examples, most of them only acknowledge one ticker and they assume you are only going to work with complete daily OHLC data.

I have read how to extend the data feed in order to add other criteria.

-https://community.backtrader.com/topic/2971/multiple-assets-with-custom-pandas-dataframe
-https://community.backtrader.com/topic/158/how-to-feed-backtrader-alternative-data/5

So far, I have an excel file with different tickers with only monthly close price and revenue figures that I will convert to a csv.

So my questions are...

a) Wich should be the best (easiest) formatting for the csv file in order to use it in backtrader ? Do I need one file per ticker with a date, price, revenue column resulting in +1000 files? Or maybe 2 files with only date or ticker header and revenue data in each row? Is it possible to use the data in just one file (two columns with a common heading)?

b) As I don't have more data, how can I tell backtrader to ignore all the missing data (O H L) or just to use the data that I have (close + rev)?

c) does it matter that the data is not daily? Say I cant test with monthly, yearly figures too?

d) I'll be working with only one strategy at a time, If i need to use more than one "data file" how can apply the criteria so the buy/sell signals check the full sample and give just one final result/graph contemplating all my "universe" of stocks.

Thank you in advance for your help.