@vladisld thank you, now it works !

@ab_trader it works, thank you !

@vladisld thank you, now it works !

I tried with

cerebro.run(stdstats=False)

But I received following error:

Traceback (most recent call last):
  File "C:/Users/marketwizard/PycharmProjects/MW_Backtests/EMA_universeV2/main.py", line 262, in <module>
    strategies = cerebro.run(stdstats=False)
  File "C:\Users\marketwizard\PycharmProjects\Algotrading_libraries1\lib\site-packages\backtrader\cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "C:\Users\marketwizard\PycharmProjects\Algotrading_libraries1\lib\site-packages\backtrader\cerebro.py", line 1257, in runstrategies
    strat._addanalyzer(ancls, *anargs, **ankwargs)
  File "C:\Users\marketwizard\PycharmProjects\Algotrading_libraries1\lib\site-packages\backtrader\lineseries.py", line 461, in __getattr__
    return getattr(self.lines, name)
AttributeError: 'Lines_LineSeries_LineIterator_DataAccessor_Strateg' object has no attribute '_addanalyzer'

I modified the code in accordance to your recommandation:

• I moved the creation of the cerebro instance, the "run" and "addstrategy" method into the loop.

Then, when I run the code, the backtests results (and the plot) for the first stock in the loop are generated, then I receive the following error:

Traceback (most recent call last):
  File "C:/Users/marketwizard/PycharmProjects/MW_Backtests/EMA_universeV2/main.py", line 262, in <module>
    strategies = cerebro.run()
  File "C:\Users\marketwizard\PycharmProjects\Algotrading_libraries1\lib\site-packages\backtrader\cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "C:\Users\marketwizard\PycharmProjects\Algotrading_libraries1\lib\site-packages\backtrader\cerebro.py", line 1238, in runstrategies
    strat._addobserver(False, observers.Broker)
  File "C:\Users\marketwizard\PycharmProjects\Algotrading_libraries1\lib\site-packages\backtrader\lineseries.py", line 461, in __getattr__
    return getattr(self.lines, name)
AttributeError: 'Lines_LineSeries_LineIterator_DataAccessor_Strateg' object has no attribute '_addobserver'

Process finished with exit code 1

Here the code with the modifications described above

import backtrader as bt
import pandas as pd
import os.path
import sys
from datetime import datetime, timedelta, date
import math

period = 3650
strategyResults = {}
lastBuy = None

icap = 10000

tickers =['SH', 'VXX', 'EEM', 'QQQ', 'PSQ', 'XLF', 'GDX', 'HYG', 'EFA', 'IAU', 'XOP', 'IWM', 'FXI', 'SLV', 'USO', 'XLE', 'IEMG', 'AMLP', 'EWZ', 'XLK', 'XLI', 'VWO', 'GLD', 'XLP', 'JNK', 'EWJ', 'XLU', 'VEA', 'IEFA', 'XLV', 'PFF', 'VIXY', 'TLT', 'GDXJ', 'LQD', 'XLB', 'BKLN', 'XLY', 'SMH', 'OIH', 'ASHR', 'RSX', 'MCHI', 'VTI', 'EWH', 'SPLV', 'KRE', 'IVV', 'DIA', 'IEF', 'EZU', 'EWT', 'SPDW', 'VOO', 'SCHF', 'EWY', 'MYY', 'DOG', 'EUM']

data_path = r"C:\XXX"

# define the resolution(s) of the chart(s) & the strategy
timeframes = {
    '1D': 1
}

# New Class to define the content of the strategy
class EMAStack(bt.Strategy):
    # Define the parameters of the strategy
    params = (
        ('portfolio_expo', 0.10),  # Max 15% of the Portfolio per trade
        ('trade_risk', 0.02),  # Max 2% risk per trade (stop loss)
        ('atrdist', 3.0)  # ATR based Stop loss distance
    )

    def notify_order(self, order):
        if order.status == order.Completed:
            pass

        if not order.alive():
            self.order = None  # indicate no order is pending

    # Initialize the elements which are needed for the strategy (indicators, etc...)
    def __init__(self):

        # Define the indicators
        self.ema50 = bt.indicators.EMA(self.data.close, period=50)
        self.ema200 = bt.indicators.EMA(self.data.close, period=200)
        self.atr = bt.indicators.ATR(period=14)

        # self.log_pnl = []

        # Define the crossover signals
        self.bull_cross = bt.indicators.CrossOver(self.ema50, self.ema200)
        self.bull_cross.plotinfo.subplot = False

        self.bear_cross = bt.indicators.CrossOver(self.ema200, self.ema50)
        self.bear_cross.plotinfo.subplot = False

    def start(self):
        self.order = None  # sentinel to avoid operations on pending order
        self.curpos = None

    def prenext(self):
        self.next()

    def next(self):

        # Get the Amount of cash in the Portfolio
        cash = self.broker.get_cash()

        if self.order:
            return  # pending order execution

        if not self.position:  # check if we already have an open position on the stock

            if self.bull_cross > 0.0:

                # Calculation of the Stock Qty to buy depending on our risk strategy
                pdist = self.atr[0] * self.p.atrdist
                self.pstop = self.data.close[0] - pdist
                qty = math.floor((cash * self.p.trade_risk) / pdist)

                portfolio_exposure_calc = qty * self.data.close[0]
                portfolio_exposure_strategy = cash * self.p.portfolio_expo

                if portfolio_exposure_calc <= portfolio_exposure_strategy:
                    self.order = self.buy(size=qty)
                else:
                    qty = math.floor(portfolio_exposure_strategy / self.data.close[0])
                    self.order = self.buy(size=qty)

                '''
            elif self.bear_cross > 0.0:

                # Calculation of the Stock Qty to buy depending on our risk strategy
                pdist = self.atr[0] * self.p.atrdist
                self.pstop = self.data.close[0] - pdist
                qty = math.floor((cash * self.p.trade_risk) / pdist)

                portfolio_exposure_calc = qty * self.data.close[0]
                portfolio_exposure_strategy = cash * self.p.portfolio_expo

                if portfolio_exposure_calc <= portfolio_exposure_strategy:
                    self.order = self.sell(size=qty)
                else:
                    qty = math.floor(portfolio_exposure_strategy / self.data.close[0])
                    self.order = self.sell(size=qty)
                '''

        else:  # in the market
            pclose = self.data.close[0]
            pstop = self.pstop

            # Add detection if we are already short or long
            if pclose < pstop or self.bear_cross or self.bull_cross:
                self.close()  # stop met - get out
            else:
                pdist = self.atr[0] * self.p.atrdist
                # Update only if greater than
                self.pstop = max(pstop, pclose - pdist)

'''
    def notify_trade(self, trade):
        date = self.data.datetime.datetime()
        if trade.isclosed:
            print('-' * 32, ' NOTIFY TRADE ', '-' * 32)
            print('{}, Avg Price: {}, Profit, Gross {}, Net {}'.format(
                date,
                trade.price,
                round(trade.pnl, 2),
                round(trade.pnlcomm, 2)))
'''

def printSQN(analyzer):
    sqn = round(analyzer.sqn, 2)
    print('SQN: {}'.format(sqn))

def pretty_print(format, *args):
    print(format.format(*args))

def exists(object, *properties):
    for property in properties:
        if not property in object: return False
        object = object.get(property)
    return True

def printTradeAnalysis(cerebro, analyzers):
    format = "  {:<24} : {:<24}"
    NA     = '-'

    print('Backtesting Results')
    if hasattr(analyzers, 'ta'):
        ta = analyzers.ta.get_analysis()

        openTotal         = ta.total.open          if exists(ta, 'total', 'open'  ) else None
        closedTotal       = ta.total.closed        if exists(ta, 'total', 'closed') else None
        wonTotal          = ta.won.total           if exists(ta, 'won',   'total' ) else None
        lostTotal         = ta.lost.total          if exists(ta, 'lost',  'total' ) else None

        streakWonLongest  = ta.streak.won.longest  if exists(ta, 'streak', 'won',  'longest') else None
        streakLostLongest = ta.streak.lost.longest if exists(ta, 'streak', 'lost', 'longest') else None

        pnlNetTotal       = ta.pnl.net.total       if exists(ta, 'pnl', 'net', 'total'  ) else None
        pnlNetAverage     = ta.pnl.net.average     if exists(ta, 'pnl', 'net', 'average') else None

        pretty_print(format, 'Open Positions', openTotal   or NA)
        pretty_print(format, 'Closed Trades',  closedTotal or NA)
        pretty_print(format, 'Winning Trades', wonTotal    or NA)
        pretty_print(format, 'Loosing Trades', lostTotal   or NA)
        print('\n')

        pretty_print(format, 'Longest Winning Streak',   streakWonLongest  or NA)
        pretty_print(format, 'Longest Loosing Streak',   streakLostLongest or NA)
        pretty_print(format, 'Strike Rate (Win/closed)', (wonTotal / closedTotal) * 100 if wonTotal and closedTotal else NA)
        print('\n')

        pretty_print(format, 'Inital Portfolio Value', '${}'.format(icap))
        pretty_print(format, 'Final Portfolio Value',  '${}'.format(cerebro.broker.getvalue()))
        pretty_print(format, 'Net P/L',                '${}'.format(round(pnlNetTotal,   2)) if pnlNetTotal   else NA)
        pretty_print(format, 'P/L Average per trade',  '${}'.format(round(pnlNetAverage, 2)) if pnlNetAverage else NA)
        print('\n')

    if hasattr(analyzers, 'drawdown'):
        pretty_print(format, 'Drawdown', '${}'.format(analyzers.drawdown.get_analysis()['drawdown']))
    if hasattr(analyzers, 'sharpe'):
        pretty_print(format, 'Sharpe Ratio:', analyzers.sharpe.get_analysis()['sharperatio'])
    if hasattr(analyzers, 'vwr'):
        pretty_print(format, 'VRW', analyzers.vwr.get_analysis()['vwr'])
    if hasattr(analyzers, 'sqn'):
        pretty_print(format, 'SQN', analyzers.sqn.get_analysis()['sqn'])
    print('\n')

    print('Transactions')
    format = "  {:<24} {:<24} {:<16} {:<8} {:<8} {:<16}"
    pretty_print(format, 'Date', 'Amount', 'Price', 'SID', 'Symbol', 'Value')
    for key, value in analyzers.txn.get_analysis().items():
        pretty_print(format, key.strftime("%Y/%m/%d %H:%M:%S"), value[0][0], value[0][1], value[0][2], value[0][3], value[0][4])

if __name__ == '__main__':

    for ticker in tickers:
        cerebro = bt.Cerebro()

        endDate = date(2021, 1, 10)
        fromDate = (endDate - timedelta(days=period))

        startDate = fromDate.strftime('%Y-%m-%d')
        filename = '%s_%s_%s.txt' % (ticker, startDate, endDate)

        datapath = os.path.join(data_path, filename)
        print(os.path.abspath(datapath))

        #'''
        if not os.path.isfile(datapath):
            print('file: %s not found' % filename)
            sys.exit()
            #'''

        data = bt.feeds.YahooFinanceCSVData(
            dataname=datapath,
            # Do not pass values before this date
            fromdate=datetime(fromDate.year, fromDate.month, fromDate.day),
            # Do not pass values before this date
            todate=datetime(datetime.today().year, datetime.today().month, datetime.today().day),
            # Do not pass values after this date
            reverse=False)

        cerebro.adddata(data)
        # Set the Cash for the Strategy
        cerebro.broker.setcash(icap)
        # Set the comissions
        cerebro.broker.setcommission(commission=0.005)


        # Add the analyzers we are interested in
        cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name='ta')
        cerebro.addanalyzer(bt.analyzers.DrawDown, _name='drawdown')
        cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='sharpe', riskfreerate=0.0, annualize=True, timeframe=bt.TimeFrame.Days)
        cerebro.addanalyzer(bt.analyzers.VWR, _name='vwr')
        cerebro.addanalyzer(bt.analyzers.SQN, _name='sqn')
        cerebro.addanalyzer(bt.analyzers.Transactions, _name='txn')
        cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')

        cerebro.addstrategy(EMAStack)

        # Run over everything
        strategies = cerebro.run()
        EMAStack = strategies[0]

        # print the analyzers
        printTradeAnalysis(cerebro, EMAStack.analyzers)

        cerebro.plot(style='candlestick', barup='green', bardown='red')

@vladisld thank you for your answer.

I went through the documentations and the article from backtest-rookies and I also tested their code.

It seems that it is the same portfolio which is investing on every FX pair

What I'm trying to do is a bit different:

I want to backtest my strategy on each stock in order to generate the KPI's for each stock individually (and plot them idivually).
And in the next steps, the goal would be to generate a table / file with datas like:

'AAPL' | strike rate = 24% | sharpe ratio = 0.36 | final portfolio value = XXX
'JNJ' | strike rate = 35% | sharpe ratio = 0.52 | final portfolio value = XXX
'AMZN' | strike rate = 60% | sharpe ratio = 1.236 | final portfolio value = XXX
.....
...

Hello,

I'm currently triying to test a strategy over a list of stocks (30+) and then generate the results of the strategy for each stock.

I tried to use a for loop to go through every stock and get the results, but it doesn't work.
The code only prints the results for the first stock in the list.

Here ist the code:

import backtrader as bt
import os.path
import sys
from datetime import datetime, timedelta
import math
import warnings

period = 3650
strategyResults = {}
lastBuy = None
optimization = True

tickers =['SH', 'VXX', 'EEM', 'QQQ', 'PSQ', 'XLF', 'GDX', 'HYG', 'EFA', 'IAU', 'XOP', 'IWM', 'FXI', 'SLV', 'USO', 'XLE', 'IEMG', 'AMLP', 'EWZ', 'XLK', 'XLI', 'VWO', 'GLD', 'XLP', 'JNK', 'EWJ', 'XLU', 'VEA', 'IEFA', 'XLV', 'PFF', 'VIXY', 'TLT', 'GDXJ', 'LQD', 'XLB', 'BKLN', 'XLY', 'SMH', 'OIH', 'ASHR', 'RSX', 'MCHI', 'VTI', 'EWH', 'SPLV', 'KRE', 'IVV', 'DIA', 'IEF', 'EZU', 'EWT', 'SPDW', 'VOO', 'SCHF', 'EWY', 'MYY', 'DOG', 'EUM']

data_path = r"C:\Users\XXXXX"

# define the resolution(s) of the chart(s) & the strategy
timeframes = {
    '1D': 1
}

# New Class to define the content of the strategy
class EMAStack(bt.Strategy):
    # Define the parameters of the strategy
    params = (
        ('portfolio_expo', 0.10),  # Max 15% of the Portfolio per trade
        ('trade_risk', 0.02),  # Max 2% risk per trade (stop loss)
        ('atrdist', 3.0)  # ATR based Stop loss distance
    )

    def notify_order(self, order):
        if order.status == order.Completed:
            pass

        if not order.alive():
            self.order = None  # indicate no order is pending

    # Initialize the elements which are needed for the strategy (indicators, etc...)
    def __init__(self):

        # Define the indicators
        self.ema50 = bt.indicators.EMA(self.data.close, period=10)
        self.ema200 = bt.indicators.EMA(self.data.close, period=30)
        self.atr = bt.indicators.ATR(period=14)

        # Define the crossover signals
        self.bull_cross = bt.indicators.CrossOver(self.ema50, self.ema200)
        self.bull_cross.plotinfo.subplot = False

        self.bear_cross = bt.indicators.CrossOver(self.ema200, self.ema50)
        self.bear_cross.plotinfo.subplot = False

    def start(self):
        self.order = None  # sentinel to avoid operations on pending order

    def prenext(self):
        self.next()

    def next(self):

        # Get the Amount of cash in the Portfolio
        cash = self.broker.get_cash()

        if self.order:
            return  # pending order execution

        if not self.position:  # check if we already have an open position on the stock

            if self.bull_cross > 0.0:

                # Calculation of the Stock Qty to buy depending on our risk strategy
                pdist = self.atr[0] * self.p.atrdist
                self.pstop = self.data.close[0] - pdist
                qty = math.floor((cash * self.p.trade_risk) / pdist)

                portfolio_exposure_calc = qty * self.data.close[0]
                portfolio_exposure_strategy = cash * self.p.portfolio_expo

                if portfolio_exposure_calc <= portfolio_exposure_strategy:
                    self.order = self.buy(size=qty)
                else:
                    qty = math.floor(portfolio_exposure_strategy / self.data.close[0])
                    self.order = self.buy(size=qty)

            elif self.bear_cross > 0.0:

                # Calculation of the Stock Qty to buy depending on our risk strategy
                pdist = self.atr[0] * self.p.atrdist
                self.pstop = self.data.close[0] - pdist
                qty = math.floor((cash * self.p.trade_risk) / pdist)

                portfolio_exposure_calc = qty * self.data.close[0]
                portfolio_exposure_strategy = cash * self.p.portfolio_expo

                if portfolio_exposure_calc <= portfolio_exposure_strategy:
                    self.order = self.sell(size=qty)
                else:
                    qty = math.floor(portfolio_exposure_strategy / self.data.close[0])
                    self.order = self.sell(size=qty)


        else:  # in the market
            pclose = self.data.close[0]
            pstop = self.pstop

            # Add detection if we are already short or long
            if pclose < pstop or self.bear_cross or self.bull_cross:
                self.close()  # stop met - get out
            else:
                pdist = self.atr[0] * self.p.atrdist
                # Update only if greater than
                self.pstop = max(pstop, pclose - pdist)
    '''
    def notify_trade(self, trade):
        date = self.data.datetime.datetime()
        if trade.isclosed:
            print('-' * 32, ' NOTIFY TRADE ', '-' * 32)
            print('{}, Avg Price: {}, Profit, Gross {}, Net {}'.format(
                date,
                trade.price,
                round(trade.pnl, 2),
                round(trade.pnlcomm, 2)))
                '''

def printTradeAnalysis(analyzer):
    '''
    Function to print the Technical Analysis results in a nice format.
    '''
    # Get the results we are interested in

    total_open = analyzer.total.open
    total_closed = analyzer.total.closed
    total_won = analyzer.won.total
    total_lost = analyzer.lost.total
    win_streak = analyzer.streak.won.longest
    lose_streak = analyzer.streak.lost.longest
    pnl_net = round(analyzer.pnl.net.total, 2)
    strike_rate = round(((total_won / total_closed) * 100), 2)
    profit_factor = round((total_won / total_lost), 2)

    # Designate the rows
    h1 = ['Total Open', 'Total Closed', 'Total Won', 'Total Lost']
    h2 = ['Strike Rate', 'Win Streak', 'Losing Streak', 'PnL Net']

    r1 = [total_open, total_closed, total_won, total_lost]
    r2 = [strike_rate, win_streak, lose_streak, pnl_net]

    # Check which set of headers is the longest.
    if len(h1) > len(h2):
        header_length = len(h1)
    else:
        header_length = len(h2)
    # Print the rows
    print_list = [h1, r1, h2, r2]
    row_format = "{:<15}" * (header_length + 1)
    print("Trade Analysis Results:")

    for row in print_list:
        print(row_format.format('', *row))

    print('Profit Factor: {}'.format(profit_factor))


def printSQN(analyzer):
    sqn = round(analyzer.sqn, 2)
    print('SQN: {}'.format(sqn))

if __name__ == '__main__':
    cerebro = bt.Cerebro()

    for ticker in tickers:


        endDate = datetime.today().strftime('%Y-%m-%d')
        fromDate = (datetime.today() - timedelta(days=period))
        startDate = fromDate.strftime('%Y-%m-%d')
        filename = '%s_%s_%s.txt' % (ticker, startDate, endDate)

        datapath = os.path.join(data_path, filename)
        print(os.path.abspath(datapath))

        #'''
        if not os.path.isfile(datapath):
            print('file: %s not found' % filename)
            sys.exit()
            #'''

        data = bt.feeds.YahooFinanceCSVData(
            dataname=datapath,
            # Do not pass values before this date
            fromdate=datetime(fromDate.year, fromDate.month, fromDate.day),
            # Do not pass values before this date
            todate=datetime(datetime.today().year, datetime.today().month, datetime.today().day),
            # Do not pass values after this date
            reverse=False)

        cerebro.adddata(data)
        # Set the Cash for the Strategy
        cerebro.broker.setcash(10000)
        # Set the comissions
        cerebro.broker.setcommission(commission=0.005)

        # Add the analyzers we are interested in
        cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name='ta')
        cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
        cerebro.addanalyzer(bt.analyzers.AnnualReturn, _name="annualreturn")
        cerebro.addanalyzer(bt.analyzers.PyFolio, _name="pyfolio")

    cerebro.addstrategy(EMAStack)

    # Run over everything
    strategies = cerebro.run()
    EMAStack = strategies[0]
    #cerebro.run()

    # print the analyzers
    printTradeAnalysis(EMAStack.analyzers.ta.get_analysis())
    printSQN(EMAStack.analyzers.sqn.get_analysis())

    print("Final Portfolio Value: %.2f" % cerebro.broker.getvalue())

I hope that someone can help

@rajanprabu I already test this code and its not working for me, that's why I opened this topic

Hello ab_trader,

thanks for the quick reply !
did you have a sample code for using this datafeed ?

Hello,

I'm pretty new to Python coding and Backtrader.
However I have done some backtests using the Alpaca API and it worked without to much problems.

I would to use the Alpha-Vantage API because they provide not only stock data, but also FOREX and Crypto.

First I tried the Code I found here:
https://backtest-rookies.com/2019/01/04/backtrader-alpha-vantage-data-direct-ingest/

from alpha_vantage.timeseries import TimeSeries
import pandas as pd
import numpy as np
import backtrader as bt
from datetime import datetime

# IMPORTANT!
# ----------
# Register for an API at:
# https://www.alphavantage.co/support/#api-key
# Then insert it here.
Apikey = 'XXXXX'


def alpha_vantage_eod(symbol_list, compact=False, debug=False, *args, **kwargs):
    '''
    Helper function to download Alpha Vantage Data.

    This will return a nested list with each entry containing:
        [0] pandas dataframe
        [1] the name of the feed.
    '''
    data_list = list()

    size = 'compact' if compact else 'full'

    for symbol in symbol_list:

        if debug:
            print('Downloading: {}, Size: {}'.format(symbol, size))

        # Submit our API and create a session
        alpha_ts = TimeSeries(key=Apikey, output_format='pandas')

        data, meta_data = alpha_ts.get_daily(symbol=symbol, outputsize=size)

        #Convert the index to datetime.
        data.index = pd.to_datetime(data.index)
        data.columns = ['Open', 'High', 'Low', 'Close','Volume']

        if debug:
            print(data)

        data_list.append((data, symbol))

    return data_list

class TestStrategy(bt.Strategy):

    def __init__(self):

        pass

    def next(self):

        for i, d in enumerate(self.datas):

            bar = len(d)
            dt = d.datetime.datetime()
            dn = d._name
            o = d.open[0]
            h = d.high[0]
            l = d.low[0]
            c = d.close[0]
            v = d.volume[0]


            print('{} Bar: {} | {} | O: {} H: {} L: {} C: {} V:{}'.format(dt, bar,dn,o,h,l,c,v))


# Create an instance of cerebro
cerebro = bt.Cerebro()

# Add our strategy
cerebro.addstrategy(TestStrategy)

# Download our data from Alpha Vantage.
symbol_list = ['LGEN.L','LLOY.L']
data_list = alpha_vantage_eod(
                symbol_list,
                compact=False,
                debug=False)

for i in range(len(data_list)):

    data = bt.feeds.PandasData(
                dataname=data_list[i][0], # This is the Pandas DataFrame
                name=data_list[i][1], # This is the symbol
                timeframe=bt.TimeFrame.Days,
                compression=1,
                fromdate=datetime(2018,1,1),
                todate=datetime(2019,1,1)
                )

    #Add the data to Cerebro
    cerebro.adddata(data)

print('Starting to run')
# Run the strategy
cerebro.run()

Unfortunately it didn't work. I wasn't able to display any data with it.
And yes, I used my API - key (which is working, i tested it in another code)

I thought that the problem came from the Pandas dataframe from Alpha-Vantage (maybe not supported anymore)

I tried different things and I done quiet a lot of research in the internet and I can't find any suitable solution.

I also tried to request JSON datas and convert them to pandas or CSV, unfortunately this was also not working.

But maybe someone can help with the code above.

Thanks a lot in adavance
marketwizard