:Here a part of the source code with the timeframe/compression setting

def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime(2016, 11, 25) # datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime(2016, 12, 02) # datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Create the 1st data
    tframes = dict(
        secondes=bt.TimeFrame.Seconds,
        minutes=bt.TimeFrame.Minutes,
        days=bt.TimeFrame.Days,
        weeks=bt.TimeFrame.Weeks,
        months=bt.TimeFrame.Months,
        years=bt.TimeFrame.Years)

    # Create the 1st data
    """
    data0 = btfeeds.YahooFinanceCSVData(
        dataname=args.data0,
        fromdate=fromdate,
        todate=todate)
    """
    data0 = btfeeds.GenericCSVData(
        dataname=args.data0,

        fromdate=fromdate,
        todate=todate,

        nullvalue=0.0,

        dtformat=('%Y-%m-%d %H:%M:%S'),
        datetime=0,
        high=2,
        low=3,
        open=1,
        close=4,
        volume=5,
        openinterest=-1,
    )

    # Add the 1st data to cerebro
    cerebro.adddata(data0)

    # Create the 2nd data
    """
    data1 = btfeeds.YahooFinanceCSVData(
        dataname=args.data1,
        fromdate=fromdate,
        todate=todate)
    """
    data1 = btfeeds.GenericCSVData(
        dataname=args.data1,

        fromdate=fromdate,
        todate=todate,

        nullvalue=0.0,

        dtformat=('%Y-%m-%d %H:%M:%S'),
        datetime=0,
        high=2,
        low=3,
        open=1,
        close=4,
        volume=5,
        openinterest=-1,
    )

    # Add the 2nd data to cerebro
    cerebro.adddata(data1)


    cerebro.resampledata(data0,timeframe=tframes[args.timeframe], compression=args.compression)
    # Create the 2nd data
    # Add the 2nd data to cerebro
    #cerebro.adddata(data1)
    cerebro.resampledata(data1,timeframe=tframes[args.timeframe], compression=args.compression)

    # Add the strategy
    cerebro.addstrategy(PairTradingStrategy,
                        period=args.period,
                        stake=args.stake)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcash(args.cash)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcommission(commission=args.commperc)

    # And run it
    cerebro.run(runonce=not args.runnext,
                preload=not args.nopreload,
                oldsync=args.oldsync)

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False)


def parse_args():
    parser = argparse.ArgumentParser(description='MultiData Strategy')

    parser.add_argument('--data0', '-d0',
                        default='intra-DDD.csv',
                        help='1st data into the system')

    parser.add_argument('--data1', '-d1',
                        default='intra-SSYS.csv',
                        help='2nd data into the system')

    parser.add_argument('--fromdate', '-f',
                        default='1997-01-01',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        default='1998-06-01',
                        help='Starting date in YYYY-MM-DD format')

    group = parser.add_mutually_exclusive_group()
    group.add_argument('--tframe', default='years', required=False,
                       choices=['days', 'weeks', 'months', 'years'],
                       help='TimeFrame for the returns/Sharpe calculations')

    group.add_argument('--legacyannual', action='store_true',
                       help='Use legacy annual return analyzer')


    pgroup = parser.add_mutually_exclusive_group(required=False)

    pgroup.add_argument('--replay',
                        required=False, action='store_true',
                        help='replay to chosen timeframe')

    pgroup.add_argument('--resample', default = True,
                        required=False, action='store_true',
                        help='resample to chosen timeframe')

    parser.add_argument('--timeframe', default='minutes',
                        choices=bt.TimeFrame.Names,
                        required=False, action='store',
                        help='TimeFrame for Resample/Replay')

    parser.add_argument('--compression', default=1, type=int,
                        required=False, action='store',
                        help='Compression for Resample/Replay')

    parser.add_argument('--timeframe1', default=True,
                        choices=bt.TimeFrame.Names,
                        required=False, action='store',
                        help='TimeFrame for Resample/Replay - Data1')

    parser.add_argument('--compression1', default=None, type=int,
                        required=False, action='store',
                        help='Compression for Resample/Replay - Data1')

    parser.add_argument('--period', default=10, type=int,
                        help='Period to apply to the Simple Moving Average')

    parser.add_argument('--cash', default=100000, type=int,
                        help='Starting Cash')

    parser.add_argument('--runnext', action='store_true',
                        help='Use next by next instead of runonce')

    parser.add_argument('--nopreload', action='store_true',
                        help='Do not preload the data')

    parser.add_argument('--oldsync', action='store_true',
                        help='Use old data synchronization method')

    parser.add_argument('--commperc', default=0.005, type=float,
                        help='Percentage commission (0.005 is 0.5%%')

    parser.add_argument('--stake', default=10, type=int,
                        help='Stake to apply in each operation')

    parser.add_argument('--plot', '-p', default=True, action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()


if __name__ == '__main__':
    runstrategy()

Hi Curtis,

Thank you very much for the correction. It works !!!
We can close this case.
Regards,

Hi EveryBody !!!
Hi Backtrader !!!
Does BT is support and compatible with Full real-time feeding provided by websocket ?

Does somebody have implement something like this ?

Hi Curtis,

Thank you very much for the correction. It works !!!
We can close this case.
Regards,

I would like to play with the indicator. @backtrader How can I do it ?
I'm have a lots of fun working with this plateforme.

Regards,

@cgi1 said in Make calcul with indicator:

a

Hi cgi1
thanks for your help.

I would like to do something like this :

def __init__(self):

    self.sma0 = btind.MovAv.SMA(self.data, period=12)

    self.sma1 = ((self.sma0.lines.sma(0) - self.sma0.lines.sma(1)) / 2)


def next(self):
    print(" sma1: %s" %( self.sma1[0]))

but the result I 've is "nan"

sma1: nan
sma1: nan
sma1: nan
sma1: nan
sma1: nan

Hi BackTrader !!!
How are you ?
Could you explain to me how can I use the line values to use them in math formuler ?

class MyStrategy(bt.Strategy):

params = dict(period=20)
def __init__(self):

    self.movav = btind.SimpleMovingAverage(self.data, period=self.p.period)
    self.test = ((self.movav.lines.sma(0) - self.movav.lines.sma(-2)) / 2

def next(self):
    if self.movav.lines.sma[0] > self.data.lines.close[0]:
        print('Simple Moving Average is greater than the closing price')

Regards

Hi,

I would like to test my strategy with real live data to see how it reacts.

Could you help me on that ?

Regards,

How can I generated Stochastic signal from other line like "ema of (data)" in Backtrader ?

@backtrader thx I fixed it with your help !!!

@backtrader the code is splited. Does it miss something ? I didn't undestand your question.

cerebro.resampledata(data0,timeframe=tframes[args.timeframe], compression=args.compression)
cerebro.resampledata(data1,timeframe=tframes[args.timeframe], compression=args.compression)

parser.add_argument('--timeframe', default='minutes',
choices=bt.TimeFrame.Names,
required=False, action='store',
help='TimeFrame for Resample/Replay')

parser.add_argument('--compression', default=1, type=int,
required=False, action='store',
help='Compression for Resample/Replay')

:Here a part of the source code with the timeframe/compression setting

def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime(2016, 11, 25) # datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime(2016, 12, 02) # datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Create the 1st data
    tframes = dict(
        secondes=bt.TimeFrame.Seconds,
        minutes=bt.TimeFrame.Minutes,
        days=bt.TimeFrame.Days,
        weeks=bt.TimeFrame.Weeks,
        months=bt.TimeFrame.Months,
        years=bt.TimeFrame.Years)

    # Create the 1st data
    """
    data0 = btfeeds.YahooFinanceCSVData(
        dataname=args.data0,
        fromdate=fromdate,
        todate=todate)
    """
    data0 = btfeeds.GenericCSVData(
        dataname=args.data0,

        fromdate=fromdate,
        todate=todate,

        nullvalue=0.0,

        dtformat=('%Y-%m-%d %H:%M:%S'),
        datetime=0,
        high=2,
        low=3,
        open=1,
        close=4,
        volume=5,
        openinterest=-1,
    )

    # Add the 1st data to cerebro
    cerebro.adddata(data0)

    # Create the 2nd data
    """
    data1 = btfeeds.YahooFinanceCSVData(
        dataname=args.data1,
        fromdate=fromdate,
        todate=todate)
    """
    data1 = btfeeds.GenericCSVData(
        dataname=args.data1,

        fromdate=fromdate,
        todate=todate,

        nullvalue=0.0,

        dtformat=('%Y-%m-%d %H:%M:%S'),
        datetime=0,
        high=2,
        low=3,
        open=1,
        close=4,
        volume=5,
        openinterest=-1,
    )

    # Add the 2nd data to cerebro
    cerebro.adddata(data1)


    cerebro.resampledata(data0,timeframe=tframes[args.timeframe], compression=args.compression)
    # Create the 2nd data
    # Add the 2nd data to cerebro
    #cerebro.adddata(data1)
    cerebro.resampledata(data1,timeframe=tframes[args.timeframe], compression=args.compression)

    # Add the strategy
    cerebro.addstrategy(PairTradingStrategy,
                        period=args.period,
                        stake=args.stake)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcash(args.cash)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcommission(commission=args.commperc)

    # And run it
    cerebro.run(runonce=not args.runnext,
                preload=not args.nopreload,
                oldsync=args.oldsync)

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False)


def parse_args():
    parser = argparse.ArgumentParser(description='MultiData Strategy')

    parser.add_argument('--data0', '-d0',
                        default='intra-DDD.csv',
                        help='1st data into the system')

    parser.add_argument('--data1', '-d1',
                        default='intra-SSYS.csv',
                        help='2nd data into the system')

    parser.add_argument('--fromdate', '-f',
                        default='1997-01-01',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        default='1998-06-01',
                        help='Starting date in YYYY-MM-DD format')

    group = parser.add_mutually_exclusive_group()
    group.add_argument('--tframe', default='years', required=False,
                       choices=['days', 'weeks', 'months', 'years'],
                       help='TimeFrame for the returns/Sharpe calculations')

    group.add_argument('--legacyannual', action='store_true',
                       help='Use legacy annual return analyzer')


    pgroup = parser.add_mutually_exclusive_group(required=False)

    pgroup.add_argument('--replay',
                        required=False, action='store_true',
                        help='replay to chosen timeframe')

    pgroup.add_argument('--resample', default = True,
                        required=False, action='store_true',
                        help='resample to chosen timeframe')

    parser.add_argument('--timeframe', default='minutes',
                        choices=bt.TimeFrame.Names,
                        required=False, action='store',
                        help='TimeFrame for Resample/Replay')

    parser.add_argument('--compression', default=1, type=int,
                        required=False, action='store',
                        help='Compression for Resample/Replay')

    parser.add_argument('--timeframe1', default=True,
                        choices=bt.TimeFrame.Names,
                        required=False, action='store',
                        help='TimeFrame for Resample/Replay - Data1')

    parser.add_argument('--compression1', default=None, type=int,
                        required=False, action='store',
                        help='Compression for Resample/Replay - Data1')

    parser.add_argument('--period', default=10, type=int,
                        help='Period to apply to the Simple Moving Average')

    parser.add_argument('--cash', default=100000, type=int,
                        help='Starting Cash')

    parser.add_argument('--runnext', action='store_true',
                        help='Use next by next instead of runonce')

    parser.add_argument('--nopreload', action='store_true',
                        help='Do not preload the data')

    parser.add_argument('--oldsync', action='store_true',
                        help='Use old data synchronization method')

    parser.add_argument('--commperc', default=0.005, type=float,
                        help='Percentage commission (0.005 is 0.5%%')

    parser.add_argument('--stake', default=10, type=int,
                        help='Stake to apply in each operation')

    parser.add_argument('--plot', '-p', default=True, action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()


if __name__ == '__main__':
    runstrategy()