Test a strategy over a list of stocks (50+)

marketwizard

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

vladisld

@marketwizard said in Test a strategy over a list of stocks (50+):

self.ema50 = bt.indicators.EMA(self.data.close, period=10)

self.pstop = self.data.close[0] - pdist

self.order = self.buy(size=qty)

You strategy is only using the first data feed added. self.data is a shortcut for the first datafeed. self.buy(size=qty) will also create the buy order for the first data feed.

Please take a look at the docs:

https://www.backtrader.com/docu/concepts/#shortcuts-for-data-feeds

explain the various shortcuts available for the strategy

https://www.backtrader.com/docu/strategy/#reference-strategy

shows how to pass the arbitrary data feed (and not only the first one) to the buy method.

One more useful article explaining how to work with multiple data feeds:

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

marketwizard

@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:

vladisld

In this case you should have created the Cerebro instance for each ticket and call its run method in the loop. The code you've presented above just adds multiple symbols to the same Cerebro instance and runs all of them together afterwards. Please correct me if I'm wrong

marketwizard

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

Could you please try to run the Cerebro engine using:

cerebro.run(stdstats=False)

marketwizard

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'

vladisld

@marketwizard said in Test a strategy over a list of stocks (50+):

cerebro.addstrategy(EMAStack)

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

You are overriding the EMAStack name - which should be a class of your strategy with the strategy instance returned from the Cerebro.run() method. So the next iteration in the cerebro.addstrategy(EMAStack) the strategy instance is passed instead of strategy class.

marketwizard

@vladisld thank you, now it works !