Hi,

I am trying to access broker params values from within the strategy. Depending on they way I try to get the coc value, sometimes I get the actual value and other the default value. Can someone please explain the behaviour?

Many thanks

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import backtrader as bt
import pandas as pd
import datetime

# Create a Strategy
class TestStrategy(bt.Strategy):

    def __init__(self):
        params_dict = self.broker.params._getpairs()
        print(type(self.broker.params))
        print("COC: {}, {}, {}".format(self.broker.params.coc, params_dict['coc'], self.broker.params._get('coc')))


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy with parameters
    cerebro.addstrategy(TestStrategy)

    df1 = pd.DataFrame({'Close': list(range(1,11))}, index=pd.date_range(start='1/1/2018', periods=10))
    cerebro.adddata(bt.feeds.PandasData(dataname=df1, nocase=True))

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)
    cerebro.broker.set_coc(True)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run(runonce=False, preload=False)

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

Starting Portfolio Value: 100000.00
<class 'backtrader.metabase.AutoInfoClass_BrokerBase_BackBroker'>
COC: True, False, True
Final Portfolio Value: 100000.00

Hi,

I am trying to combine SessionFiller and Resampler but it does not seem to work no matter which order these are added. Independently both work correctly.

The data set (just showing close) is

,close
2018-08-08 09:01:01,4
2018-08-08 09:02:01,5
2018-08-08 09:03:01,6
2018-08-08 09:06:01,7
2018-08-08 09:07:01,8
2018-08-08 09:08:01,9
2018-08-08 09:09:01,10
2018-08-08 09:10:01,11
2018-08-08 09:11:01,12
2018-08-08 09:12:01,13

and I would expect to get something like

2018-08-08 09:02:00, 4.0
2018-08-08 09:04:00, 6.0
2018-08-08 09:06:00, 6.0
2018-08-08 09:08:00, 8.0
2018-08-08 09:10:00, 10.0
2018-08-08 09:12:00, 12.0
2018-08-08 09:14:00, 13.0

Thanks

import backtrader as bt
import sys
import os
import datetime

class StrategyBidAsk(bt.Strategy):

    def start(self):
        self.counter = 0

    def next(self):
        self.counter += 1
        output_str = ""
        for i in range(len(self.datas)):
            output_str += "{}: {}, {}|".format(self.datas[i]._name, self.datas[i].datetime.datetime(0), self.datas[i].lines.close[0])
        output_str = output_str[:-1]
        print(output_str)

def main(argv):

    folder = "data"
    file = 'Toy_Ask_new.csv'
    cash = 100000.0

    cerebro = bt.Cerebro()
    cerebro.broker.setcash(cash)
    cerebro.broker.set_shortcash(False)
    cerebro.broker.setcommission(commission=0)
    cerebro.broker.set_coc(False)

    data = bt.feeds.GenericCSVData(
            dataname=os.path.join(folder, file),
            dtformat='%Y-%m-%d %H:%M:%S', # default
            datetime=0,         # default
            time=-1,            # default
            close=1,
            high=2,
            low=3,
            open=4,
            volume=5,           # default
            openinterest=-1,    # default for not present
            sessionstart=datetime.time(9, 0),
            sessionend=datetime.time(16, 0),
            timeframe=bt.TimeFrame.Minutes,
            compression=1)      # default

    data.addfilter(bt.filters.SessionFilter)
    data.addfilter(bt.filters.SessionFiller)
    data.addfilter(bt.ResamplerMinutes, compression=2)
    cerebro.adddata(data, name=os.path.splitext(file)[0])

    idx = cerebro.addstrategy(StrategyBidAsk)
    cerebro.addsizer_byidx(idx, bt.sizers.SizerFix, stake=100)
    cerebro.run(runonce=False, preload=True)


if __name__ == "__main__":
    main(sys.argv)

Thanks for your reply and help. By system you mean the strategy? Because in this case, strategy will have length 5 while indicator length 4.

# Toy_Ask: 2018-08-08 00:00:01, 3.0|Toy_Bid: 2018-08-08 00:00:01, 5.0
# MidPriceIndicator toy_mid 4.0 4.0 1 1
# Toy_Ask: 2018-08-08 00:02:01, 3.0|Toy_Bid: 2018-08-08 00:02:01, 6.0
# MidPriceIndicator toy_mid 4.5 4.0 2 2
# Toy_Ask: 2018-08-08 00:02:01, 3.0|Toy_Bid: 2018-08-08 00:03:01, 7.0
# MidPriceIndicator toy_mid 5.0 4.5 3 3
# Toy_Ask: 2018-08-08 00:04:01, 0.0|Toy_Bid: 2018-08-08 00:03:01, 7.0
# MidPriceIndicator toy_mid 3.5 4.5 3 4
# Toy_Ask: 2018-08-08 00:08:01, 1.0|Toy_Bid: 2018-08-08 00:08:01, 2.0
# MidPriceIndicator toy_mid 1.5 3.5 4 5

import backtrader as bt
import sys
import os


class StrategyBidAsk(bt.Strategy):

    def next(self):
        output_str = ""
        for i in range(len(self.datas)):
            output_str += "{}: {}, {}|".format(self.datas[i]._name, self.datas[i].datetime.datetime(0), self.datas[i].lines.close[0])
        output_str = output_str[:-1]
        print(output_str)
        for ind in self.getindicators_lines():
            line_names = ind.getlinealiases()
            for idx in range(len(line_names)):
                print("{} {} {} {} {} {}".format(ind.plotinfo.plotname or ind.__class__.__name__,
                                        line_names[idx], ind.lines[idx][0], ind.lines[idx][-1], len(ind), len(self)))


class MidPriceIndicator(bt.Indicator):
    lines = ('toy_mid',)

    def __init__(self):
        self.lines.toy_mid = (self.datas[0]+self.datas[1])/2


def main(argv):

    folder = "data"
    files = [['Toy_Ask.csv', 'Toy_Bid.csv']]
    cash = 100000.0

    cerebro = bt.Cerebro()
    cerebro.broker.setcash(cash)
    cerebro.broker.set_shortcash(False)
    cerebro.broker.setcommission(commission=0)
    cerebro.broker.set_coc(False)

    for file in files:
        if not isinstance(file, list):
            file = [file]
        data_list = []
        for i, f in enumerate(file):
            data = bt.feeds.GenericCSVData(
                    dataname=os.path.join(folder, f),
                    dtformat='%Y-%m-%d %H:%M:%S', # default
                    datetime=0,         # default
                    time=-1,            # default
                    close=1,
                    high=-1,
                    low=-1,
                    open=-1,
                    volume=-1,           # default
                    openinterest=-1,    # default for not present
                    timeframe=bt.TimeFrame.Minutes,
                    compression=1)      # default
            if i != 0 and len(file) == 2:
                data.compensate(data_list[0])
            data_list.append(data)
            cerebro.adddata(data, name=os.path.splitext(f)[0])

    idx = cerebro.addstrategy(StrategyBidAsk)
    cerebro.addsizer_byidx(idx, bt.sizers.SizerFix, stake=100)
    cerebro.addindicator(MidPriceIndicator, cerebro.datasbyname["Toy_Bid"]._getline("close"), cerebro.datasbyname["Toy_Ask"]._getline("close"))
    cerebro.run(runonce=False, preload=True)
    cerebro.plot(volume=False, numfigs=1)


if __name__ == "__main__":
    main(sys.argv)

Hi,

I would like to implement an indicator that first calculates the bid-ask midpoint on two separate minute-bar data feeds, one for bid and the other for ask. These data feeds are not synchronised i.e. there are minutes when one has value and the other does not. Although the value of the indicator is correct, its length is not. When the second feed does not have a minute bar of the first feed, it just overwrites the indicator value.

Many thanks for the help.

import backtrader as bt
import sys
import os


class StrategyBidAsk(bt.Strategy):

    def next(self):
        output_str = ""
        for i in range(len(self.datas)):
            output_str += "{}: {}, {}|".format(self.datas[i]._name, self.datas[i].datetime.datetime(0), self.datas[i].lines.close[0])
        output_str = output_str[:-1]
        print(output_str)
        for ind in self.getindicators_lines():
            line_names = ind.getlinealiases()
            for idx in range(len(line_names)):
                print("{} {} {} {} {}".format(ind.plotinfo.plotname or ind.__class__.__name__,
                                        line_names[idx], ind.lines[idx][0], ind.lines[idx][-1], len(ind)))


class MidPriceIndicator(bt.Indicator):
    lines = ('toy_mid',)

    def __init__(self):
        self.lines.toy_mid = (self.datas[0]+self.datas[1])/2


def main(argv):

    folder = "data"
    files = [['Toy_Ask.csv', 'Toy_Bid.csv']]
    cash = 100000.0

    cerebro = bt.Cerebro()
    cerebro.broker.setcash(cash)
    cerebro.broker.set_shortcash(False)
    cerebro.broker.setcommission(commission=0)
    cerebro.broker.set_coc(False)

    for file in files:
        if not isinstance(file, list):
            file = [file]
        data_list = []
        for i, f in enumerate(file):
            data = bt.feeds.GenericCSVData(
                    dataname=os.path.join(folder, f),
                    dtformat='%Y-%m-%d %H:%M:%S', # default
                    datetime=0,         # default
                    time=-1,            # default
                    close=1,
                    high=-1,
                    low=-1,
                    open=-1,
                    volume=-1,           # default
                    openinterest=-1,    # default for not present
                    timeframe=bt.TimeFrame.Minutes,
                    compression=1)      # default
            if i != 0 and len(file) == 2:
                data.compensate(data_list[0])
            data_list.append(data)
            cerebro.adddata(data, name=os.path.splitext(f)[0])

    idx = cerebro.addstrategy(StrategyBidAsk)
    cerebro.addsizer_byidx(idx, bt.sizers.SizerFix, stake=100)
    cerebro.addindicator(MidPriceIndicator, cerebro.datasbyname["Toy_Bid"]._getline("close"), cerebro.datasbyname["Toy_Ask"]._getline("close"))
    cerebro.run(runonce=False, preload=True)
    cerebro.plot(volume=False, numfigs=1)


if __name__ == "__main__":
    main(sys.argv)

# # Output
# Toy_Ask: 2018-08-08 00:00:01, 3.0|Toy_Bid: 2018-08-08 00:00:01, 5.0
# MidPriceIndicator toy_mid 4.0 4.0 1
# Toy_Ask: 2018-08-08 00:02:01, 3.0|Toy_Bid: 2018-08-08 00:02:01, 6.0
# MidPriceIndicator toy_mid 4.5 4.0 2
# Toy_Ask: 2018-08-08 00:02:01, 3.0|Toy_Bid: 2018-08-08 00:03:01, 7.0
# MidPriceIndicator toy_mid 5.0 4.5 3
# Toy_Ask: 2018-08-08 00:04:01, 0.0|Toy_Bid: 2018-08-08 00:03:01, 7.0
# MidPriceIndicator toy_mid 3.5 4.5 3
# Toy_Ask: 2018-08-08 00:08:01, 1.0|Toy_Bid: 2018-08-08 00:08:01, 2.0
# MidPriceIndicator toy_mid 1.5 3.5 4

Hi,

I understand that the concept of multiple strategies has been discussed in many threads.

If I got it correctly, since there is one broker per cerebro and the broker holds positions by data and not by (data, strategy), strategies won't work independently i.e. whatever functionality is based on position will 'work' on the total position and not just the position of the strategy itself. However, orders and trades seems to be independent per strategy.

I would be interested to have some feedback on how to manage multiple strategies. I guess:

• you can have different cerebro, one per strategy, but then communication/synchronisation won't be easy.

• or have a different sizer per strategy and have each strategy keeping track of its own position, value, etc. I am not sure whether observes, analysers, etc would work on strategy level.

I would highly appreciate any feedback and ideas on this.

Many thanks

Thanks for your prompt reply and help.

I am not questioning whether this is the right behaviour from a design/conceptual point of view.

However, it seems to me that if you want to record the highest close value since the trade opened, it is not possible with a dynamic indicator. Order executed on open of 2018-01-05 (based on signal on previous day), trade opens, p.tradeopen set to True, close on that day is 100 and on 2018-01-06 the dynamic indicator has as highest close value the value of 2018-01-06 which is 5 (instead of 100).

Unless of course, I try something like this

    def notify_trade(self, trade):
        self.dyn_highest.p.tradeopen = trade.isopen
        if trade.justopened:
            self.dyn_highest.lines.dyn_highest[0] = self.data[0]
            print("NOTE: Opening trade at price {} on date {}".format(trade.price, bt.utils.num2date(trade.dtopen)))

Hi,

I wonder regarding the dynamic indicator missing the first day a trade is opened since indicators are called before notify_order and notify_trade that are being called before next. On the following example where indicator records the highest close value for a trade, the indicator's value is updated on the 2nd day after buy. Setting coc to True does not really change something. Is there any way to change this behavior?

Thanks

import backtrader as bt
import pandas as pd

class DynamicHighest(bt.Indicator):
    lines = ('dyn_highest',)
    params = dict(tradeopen=False)

    def next(self):
        print("Indicator next")
        if self.p.tradeopen:
            self.lines.dyn_highest[0] = max(self.data[0], self.dyn_highest[-1])


class MyStrategy(bt.Strategy):
    def __init__(self):
        self.dyn_highest = DynamicHighest(data=self.datas[0].lines.close)

    def notify_order(self, order):
        if order.status == order.Completed:
            if order.isbuy():
                print("NOTE: BUY EXECUTED, {} shares at {}".format(order.size, order.executed.price))
            elif order.issell():
                print("NOTE: SELL EXECUTED, {} shares at {}".format(order.size, order.executed.price))

    def notify_trade(self, trade):
        self.dyn_highest.p.tradeopen = trade.isopen
        if trade.justopened:
            print("NOTE: Opening trade at price {} on date {}".format(trade.price, bt.utils.num2date(trade.dtopen)))

    def next(self):
        print("Before:{}, {}, {}, {}, {}".format(self.datas[0].datetime.date(0),
                                             self.datas[0].lines.close[0],
                                             self.datas[0].lines.high[0],
                                             self.dyn_highest.p.tradeopen,
                                             self.dyn_highest.lines.dyn_highest[0]))
        if self.datas[0].lines.high[0] > 0:
            self.buy()
        print("After:{}, {}, {}, {}, {}".format(self.datas[0].datetime.date(0),
                                             self.datas[0].lines.close[0],
                                             self.datas[0].lines.high[0],
                                             self.dyn_highest.p.tradeopen,
                                             self.dyn_highest.lines.dyn_highest[0]))


if __name__ == '__main__':

    # Create a cerebro entity
    cerebro = bt.Cerebro()

    cerebro.addstrategy(MyStrategy)

    df1 = pd.DataFrame({'Close': [1,2,3,4,100,5,7,6], 'Open': [0,1,2,3,99,4,6,5], 'High': [0,0,0,1,0,0,0,0]}, index=pd.date_range(start='1/1/2018', periods=8))
    cerebro.adddata(bt.feeds.PandasData(dataname=df1, nocase=True))

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)
    #cerebro.broker.set_coc(True)

    cerebro.run(runonce=False, preload=True)

Indicator next
Before:2018-01-01, 1.0, 0.0, False, nan
After:2018-01-01, 1.0, 0.0, False, nan
Indicator next
Before:2018-01-02, 2.0, 0.0, False, nan
After:2018-01-02, 2.0, 0.0, False, nan
Indicator next
Before:2018-01-03, 3.0, 0.0, False, nan
After:2018-01-03, 3.0, 0.0, False, nan
Indicator next
Before:2018-01-04, 4.0, 1.0, False, nan
After:2018-01-04, 4.0, 1.0, False, nan
Indicator next
NOTE: BUY EXECUTED, 1 shares at 99.0
NOTE: Opening trade at price 99.0 on date 2018-01-05 00:00:00
Before:2018-01-05, 100.0, 0.0, True, nan
After:2018-01-05, 100.0, 0.0, True, nan
Indicator next
Before:2018-01-06, 5.0, 0.0, True, 5.0
After:2018-01-06, 5.0, 0.0, True, 5.0
Indicator next
Before:2018-01-07, 7.0, 0.0, True, 7.0
After:2018-01-07, 7.0, 0.0, True, 7.0
Indicator next
Before:2018-01-08, 6.0, 0.0, True, 7.0
After:2018-01-08, 6.0, 0.0, True, 7.0

Hi,

I wonder whether I can use the data feed name and the line name passed as parameters within the Indicator class to retrieve the corresponding line.

In a Strategy class I can do for example

self.getdatabyname(self.params.data_name)._getline(self.params.line_name)

I understand that I could pass either the actual data/line or data and line indices but I wonder whether there is something similar to the above for the indicator class.

Thanks

Hi,

I wonder what's the recommended way to deal with missing open for some days. The default behaviour is the order to be matched with the opening price of the next day and that being nan creates problems. I understand I could use DataFiller and fill the bar setting the open equal to close for the days that is nan. Is there some other way to match the order against the close of the next day if open is not available?

Thanks for the help

Many thanks for the reply and the help.

Do you mean instead of changing the data of the indicator, change the data feed itself?

I tried that below and although the data feed changes, the moving average is not updated.

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import backtrader as bt
import pandas as pd
import datetime

# Create a Strategy
class TestStrategy(bt.Strategy):

    params = (
        ('maperiod', 2),
    )

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.ind = bt.indicators.SimpleMovingAverage(self.datas[0], period=self.params.maperiod)

    def next(self):
        if self.datas[0].datetime.date(0) == datetime.datetime(2018, 1, 6).date():
            self.datas[0] = self.datas[1]
            # del self.datas[0]
        self.log("{}, {}".format(self.datas[0].lines.close[0], self.ind.lines.sma[0]))


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy with parameters
    cerebro.addstrategy(TestStrategy, maperiod=2)

    df1 = pd.DataFrame({'Close': list(range(1,11))}, index=pd.date_range(start='1/1/2018', periods=10))
    df2 = pd.DataFrame({'Close': list(range(2,12))}, index=pd.date_range(start='1/1/2018', periods=10))
    cerebro.adddata(bt.feeds.PandasData(dataname=df1, nocase=True))
    cerebro.adddata(bt.feeds.PandasData(dataname=df2, nocase=True))

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run(runonce=False, preload=False)

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

Starting Portfolio Value: 100000.00
2018-01-02, 2.0, 1.5
2018-01-03, 3.0, 2.5
2018-01-04, 4.0, 3.5
2018-01-05, 5.0, 4.5
2018-01-06, 7.0, 5.5
2018-01-07, 8.0, 6.5
2018-01-08, 9.0, 7.5
2018-01-09, 10.0, 8.5
2018-01-10, 11.0, 9.5
Final Portfolio Value: 100000.00